Application Ingestion and Replication > Application Ingestion and Replication > Default data-type mappings

Default data-type mappings

This reference provides default data-type mappings for source applications and Amazon Redshift, Databricks, Google BigQuery, Microsoft Azure Synapse Analytics, Oracle, and Snowflake targets. When Application Ingestion and Replication generates the target data, it uses these mappings.

When you configure a target, you can optionally define data-type mapping rules to customize the default mappings of source data types to the target tables. For more information, see the target-specific topics accessed from Task details: Configure how to replicate data to the target.

If a source data type is not listed, Application Ingestion and Replication either cannot extract data from the source columns with this data type or cannot apply the extracted data to any appropriate target data type.

Adobe Analytics Source and Amazon Redshift Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with an Adobe Analytics source and an Amazon Redshift target:

Adobe Analytics Source Data Type	Amazon Redshift Target Data Type
currency(p,s), 1 <= p <= 38, 0 <= s <= 19	numeric(p,s), 1 <= p <= 38, 0 <= s <= 19
datetime(3)	timestamp without time zone
decimal(p,s), 1 <= p <= 38, 0 <= s <= 19	numeric(p,s), 1 <= p <= 38, 0 <= s <= 19
enum	binary varying(size), 264004 <= size <= 1020004
enum	character varying(65535)
enum	character varying(size), 4 <= size <= 65535
int(p,s), 1 <= p <= 38, 0 <= s <= 19	numeric(p,s), 1 <= p <= 38, 0 <= s <= 19
ordered-enum	binary varying(size), 264004 <= size <= 1020004
ordered-enum	character varying(65535)
ordered-enum	character varying(size), 4 <= size <= 65535
percent(p,s), 1 <= p <= 38, 0 <= s <= 19	numeric(p,s), 1 <= p <= 38, 0 <= s <= 19
string	binary varying(size), 264004 <= size <= 1020004
string	character varying(65535)
string	character varying(size), 4 <= size <= 65535

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure an Amazon Redshift target.

Adobe Analytics Source and Google BigQuery Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with an Adobe Analytics source and a Google BigQuery target:

Adobe Analytics Source Data Type	Google BigQuery Target Data Type
currency(p,s), 1 <= p <= 38, 0 <= s <= 19	bignumeric
datetime(3)	datetime
decimal(p,s), 1 <= p <= 38, 0 <= s <= 19	bignumeric
enum	string
int(p,s), 1 <= p <= 38, 0 <= s <= 19	bignumeric
ordered-enum	string
percent(p,s), 1 <= p <= 38, 0 <= s <= 19	bignumeric
string	string

Adobe Analytics Source and Microsoft Azure Synapse Analytics Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with an Adobe Analytics source and a Microsoft Azure Synapse Analytics target:

Adobe Analytics Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
currency(p,s), 1 <= p <= 38, 0 <= s <= 19	decimal(p,s), 1 <= p <= 38, 1 <= s <= 19
datetime(3)	datetime
decimal(p,s), 1 <= p <= 38, 0 <= s <= 19	decimal(p,s), 1 <= p <= 38, 1 <= s <= 19
enum	varchar(size), 4 <= size <= max
int(p,s), 1 <= p <= 38, 0 <= s <= 19	decimal(p,s), 1 <= p <= 38, 1 <= s <= 19
ordered-enum	varchar(size), 4 <= size <= max
percent(p,s), 1 <= p <= 38, 0 <= s <= 19	decimal(p,s), 1 <= p <= 38, 1 <= s <= 19
string	varchar(size), 4 <= size <= max

Adobe Analytics Source and Oracle Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with an Adobe Analytics source and an Oracle target:

Adobe Analytics Source Data Type	Oracle Target Data Type
currency(p,s), 1 <= p <= 38, 0 <= s <= 19	number(p,s), 1 <= p <= 38, 1 <= s <= 19
datetime(3)	timestamp(3)
decimal(p,s), 1 <= p <= 38, 0 <= s <= 19	number(p,s), 1 <= p <= 38, 1 <= s <= 19
enum	char(s char), 4 <= s <= 2000
enum	clob
int(p,s), 1 <= p <= 38, 0 <= s <= 19	number(p,s), 1 <= p <= 38, 1 <= s <= 19
ordered-enum	char(s char), 4 <= size <= 2000
ordered-enum	clob
percent(p,s), 1 <= p <= 38, 0 <= s <= 19	number(p,s), 1 <= p <= 38, 1 <= s <= 19
string	char(s char), 4 <= size <= 2000
string	clob

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure an Oracle target.

Adobe Analytics Source and Snowflake Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with an Adobe Analytics source and a Snowflake target:

Adobe Analytics Source Data Type	Snowflake Target Data Type
currency(p,0), 1 <= p <= 38	integer
currency(p,s), 1 <= p <= 38, 1 <= s <= 19	number(p,s), 1 <= p <= 38, 1 <= s <= 19
datetime(3)	datetime(3)
decimal(p,0), 1 <= p <= 38	integer
decimal(p,s), 1 <= p <= 38, 1 <= s <= 19	number(p,s), 1 <= p <= 38, 1 <= s <= 19
enum	char(size), 4 <= size <= 4192004
int(p,0), 1 <= p <= 38	integer
int(p,s), 1 <= p <= 38, 1 <= s <= 19	number(p,s), 1 <= p <= 38, 1 <= s <= 19
ordered-enum	char(size), 4 <= size <= 4192004
percent(p,0), 1 <= p <= 38	integer
percent(p,s), 1 <= p <= 38, 1 <= s <= 19	number(p,s), 1 <= p <= 38, 1 <= s <= 19
string	char(size), 4 <= size <= 16777216

Google Analytics Source and Amazon Redshift Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Google Analytics source and an Amazon Redshift target:

Google Analytics Source Data Type	Amazon Redshift Target Data Type
currency(38,18)	numeric(38,18)
date	date
float	double precision
integer	bigint
percent(38,18)	numeric(38,18)
string	character varying(65535)
time	double precision

Google Analytics Source and Databricks Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Google Analytics source and a Databricks target:

Google Analytics Source Data Type	Databricks Target Data Type
currency(38,18)	decimal(38,18)
date	string
float	double
integer	long
percent(38,18)	decimal(38,18)
string	string
time	double

Google Analytics Source and Google BigQuery Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Google Analytics source and a Google BigQuery target:

Google Analytics Source Data Type	Google BigQuery Target Data Type
currency(38,18)	bignumeric
date	date
float	float64
integer	int64
percent(38,18)	bignumeric
string	string
time	float64

Google Analytics Source and Microsoft Azure Synapse Analytics Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Google Analytics source and a Microsoft Azure Synapse Analytics target:

Google Analytics Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
currency(38,18)	decimal(38,18)
date	date
float	float
integer	bigint
percent(38,18)	decimal(38,18)
string	nvarchar(max)
time	float

Google Analytics Source and Oracle Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Google Analytics source and an Oracle target:

Google Analytics Source Data Type	Oracle Target Data Type
currency(38,18)	number(38,18)
date	date
float	binary_double
integer	number(19)
percent(38,18)	number(38,18)
string	clob
time	binary_double

Google Analytics Source and Snowflake Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Google Analytics source and a Snowflake target:

Google Analytics Source Data Type	Snowflake Target Data Type
currency(38,18)	numeric(38,18)
date	date
float	double precision
integer	bigint
percent(38,18)	numeric(38,18)
string	character varying(65535)
time	double precision

Marketo Source and Amazon Redshift Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Marketo source and an Amazon Redshift target:

Marketo Source Data Type	Amazon Redshift Target Data Type
boolean	boolean
currency(38,18)	numeric(38,18)
date	date
datetime	timestamp without time zone
email	character varying(65535)
float	double precision
integer	bigint
long	bigint
percent(38,18)	numeric(38,18)
phone	character varying(65535)
reference	character varying(65535)
score	bigint
string	character varying(65535)
text	character varying(65535)
url	character varying(65535)

Marketo Source and Databricks Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Marketo source and a Databricks target:

Marketo Source Data Type	Databricks Target Data Type
boolean	boolean
currency(38,18)	decimal(38,18)
date	string
datetime	timestamp
email	string
float	double
integer	integer
long	long
percent(38,18)	decimal(38,18)
phone	string
reference	string
score	integer
string	string
text	string
url	string

Marketo Source and Google BigQuery Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Marketo source and a Google BigQuery target:

Marketo Source Data Type	Google BigQuery Target Data Type
boolean	bool
currency(38,18)	bignumeric
date	date
datetime	datetime
email	string
float	float64
integer	int64
long	int64
percent(38,18)	bignumeric
phone	string
reference	string
score	int64
string	string
text	string
url	string

Marketo Source and Microsoft Azure Synapse Analytics Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Marketo source and a Microsoft Azure Synapse Analytics target:

Marketo Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
boolean	bit
currency(38,18)	decimal(38,18)
date	date
datetime	datetime
email	nvarchar(max)
float	float
integer	bigint
long	bigint
percent(38,18)	decimal(38,18)
phone	nvarchar(max)
reference	nvarchar(max)
score	bigint
string	nvarchar(max)
text	nvarchar(max)
url	nvarchar(max)

Marketo Source and Oracle Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Marketo source and an Oracle target:

Marketo Source Data Type	Oracle Target Data Type
boolean	char(1 char)
currency(38,18)	number(38,18)
date	date
datetime	timestamp(3)
email	clob
float	binary_double
integer	number(10)
long	number(19)
percent(38,18)	number(38,18)
phone	clob
reference	clob
score	number(10)
string	clob
text	clob
url	clob

Marketo Source and Snowflake Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Marketo source and a Snowflake target:

Marketo Source Data Type	Snowflake Target Data Type
boolean	boolean
currency(38,18)	number(38,18)
date	date
datetime	datetime(3)
email	char(16777216)
float	float
integer	integer
long	integer
percent(38,18)	number(38,18)
phone	char(16777216)
reference	char(16777216)
score	integer
string	char(16777216)
text	char(16777216)
url	char(16777216)

Microsoft Dynamics 365 Source and Amazon Redshift Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Microsoft Dynamics 365 source and a Amazon Redshift target:

Microsoft Dynamics 365 Source Data Type	Amazon Redshift Target Data Type
biginttype	bigint
datetimetype	timestamp without time zone
decimaltype(38,38)	character varying(41)
decimaltype(p,s), 1 <= p <= 38, 0 <= s <= 37	numeric(p,s), 1 <= p <= 38, 0 <= s <= 37
doubletype	double precision
filetype(precision), 1 <= p <= 134217728	binary varying(size), 1 <= s <= 1024000
imagetype(precision), 1 <= p <= 31457280	binary varying(size), 1 <= s <= 1024000
integertype	integer
managedpropertytype(precision), 1 <= p <= 10485760	character varying(size), 4 <= s <= 65535
memotype(precision), 1 <= p <= 1048576	character varying(size), 4 <= s <= 65535
moneytype(38,38)	character varying(41)
moneytype(p,s), 1 <= p <= 38, 0 <= s <= 37	numeric(p,s), 1 <= p <= 38, 0 <= s <= 37
picklisttype	integer
statetype	integer
statustype	integer
stringtype(precision), 1 <= p <= 3901	character varying(size), 4 <= s <= 15604
uniqueidentifier(16)	character(36)

Microsoft Dynamics 365 Source and Databricks Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Microsoft Dynamics 365 source and a Databricks target:

Microsoft Dynamics 365 Source Data Type	Databricks Target Data Type
biginttype	long
datetimetype	timestamp
decimaltype(p,s), 1 <= p <= 38, 0 <= s <= 38	decimal(p,s), 1 <= p <= 38, 0 <= s <= 38
doubletype	double
filetype(precision), 1 <= p <= 134217728	binary
imagetype(precision), 1 <= p <= 31457280	binary
integertype	integer
managedpropertytype(precision), 1 <= p <= 10485760	string
memotype(precision), 1 <= p <= 1048576	string
moneytype(p,s), 1 <= p <= 38, 0 <= s <= 38	decimal(p,s), 1 <= p <= 38, 0 <= s <= 38
picklisttype	integer
statetype	integer
statustype	integer
stringtype(precision), 1 <= p <= 3901	string
uniqueidentifier(16)	string

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure a Databricks target.

Microsoft Dynamics 365 Source and Google BigQuery Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Microsoft Dynamics 365 source and a Google BigQuery target:

MSD365 Source Data Type	Google BigQuery Target Data Type
biginttype	int64
datetimetype	datetime
decimaltype(10,10)	bignumeric
decimaltype(11,s), 10 <= s <= 11	bignumeric
decimaltype(12,s), 10 <= s <= 12	bignumeric
decimaltype(13,s), 10 <= s <= 13	bignumeric
decimaltype(14,s), 10 <= s <= 14	bignumeric
decimaltype(15,s), 10 <= s <= 15	bignumeric
decimaltype(16,s), 10 <= s <= 16	bignumeric
decimaltype(17,s), 10 <= s <= 17	bignumeric
decimaltype(18,s), 10 <= s <= 18	bignumeric
decimaltype(19,s), 10 <= s <= 19	bignumeric
decimaltype(20,s), 10 <= s <= 20	bignumeric
decimaltype(21,s), 10 <= s <= 21	bignumeric
decimaltype(22,s), 10 <= s <= 22	bignumeric
decimaltype(23,s), 10 <= s <= 23	bignumeric
decimaltype(24,s), 10 <= s <= 24	bignumeric
decimaltype(25,s), 10 <= s <= 25	bignumeric
decimaltype(26,s), 10 <= s <= 26	bignumeric
decimaltype(27,s), 10 <= s <= 27	bignumeric
decimaltype(28,s), 10 <= s <= 28	bignumeric
decimaltype(38,s), 10 <= s <= 38	bignumeric
decimaltype(p,s), 1 <= p <= 38, 0 <= s <= 9	numeric
decimaltype(p,s), 29 <= p <= 30, 0 <= s <= 29	bignumeric
decimaltype(p,s), 30 <= p <= 31, 0 <= s <= 30	bignumeric
decimaltype(p,s), 31 <= p <= 32, 0 <= s <= 31	bignumeric
decimaltype(p,s), 32 <= p <= 33, 0 <= s <= 32	bignumeric
decimaltype(p,s), 33 <= p <= 34, 0 <= s <= 33	bignumeric
decimaltype(p,s), 34 <= p <= 35, 0 <= s <= 34	bignumeric
decimaltype(p,s), 35 <= p <= 36, 0 <= s <= 35	bignumeric
decimaltype(p,s), 36 <= p <= 37, 0 <= s <= 36	bignumeric
decimaltype(p,s), 37 <= p <= 38, 0 <= s <= 37	bignumeric
doubletype	float64
filetype(precision), 1 <= p <= 134217728	bytes
imagetype(precision), 1 <= p <= 31457280	bytes
integertype	int64
managedpropertytype(precision), 1 <= p <= 10485760	string
memotype(precision), 1 <= p <= 1048576	string
moneytype(10,10)	bignumeric
moneytype(11,s), 10 <= s <= 11	bignumeric
moneytype(12,s), 10 <= s <= 12	bignumeric
moneytype(13,s), 10 <= s <= 13	bignumeric
moneytype(14,s), 10 <= s <= 14	bignumeric
moneytype(15,s), 10 <= s <= 15	bignumeric
moneytype(16,s), 10 <= s <= 16	bignumeric
moneytype(17,s), 10 <= s <= 17	bignumeric
moneytype(18,s), 10 <= s <= 18	bignumeric
moneytype(19,s), 10 <= s <= 19	bignumeric
moneytype(20,s), 10 <= s <= 20	bignumeric
moneytype(21,s), 10 <= s <= 21	bignumeric
moneytype(22,s), 10 <= s <= 22	bignumeric
moneytype(23,s), 10 <= s <= 23	bignumeric
moneytype(24,s), 10 <= s <= 24	bignumeric
moneytype(25,s), 10 <= s <= 25	bignumeric
moneytype(26,s), 10 <= s <= 26	bignumeric
moneytype(27,s), 10 <= s <= 27	bignumeric
moneytype(28,s), 10 <= s <= 28	bignumeric
moneytype(38,s), 10 <= s <= 38	bignumeric
moneytype(p,s), 1 <= p <= 38, 0 <= s <= 9	numeric
moneytype(p,s), 29 <= p <= 30, 0 <= s <= 29	bignumeric
moneytype(p,s), 30 <= p <= 31, 0 <= s <= 30	bignumeric
moneytype(p,s), 31 <= p <= 32, 0 <= s <= 31	bignumeric
moneytype(p,s), 32 <= p <= 33, 0 <= s <= 32	bignumeric
moneytype(p,s), 33 <= p <= 34, 0 <= s <= 33	bignumeric
moneytype(p,s), 34 <= p <= 35, 0 <= s <= 34	bignumeric
moneytype(p,s), 35 <= p <= 36, 0 <= s <= 35	bignumeric
moneytype(p,s), 36 <= p <= 37, 0 <= s <= 36	bignumeric
moneytype(p,s), 37 <= p <= 38, 0 <= s <= 37	bignumeric
picklisttype	int64
statetype	int64
statustype	int64
stringtype(precision), 1 <= p <= 3901	string
uniqueidentifier(16)	string

Microsoft Dynamics 365 Source and Microsoft Azure Synapse Analytics Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Microsoft Dynamics 365 source and a Microsoft Azure Synapse Analytics target:

MSD365 Source Data Type	Microsoft Azure SQL Data Warehouse or Synapse Analytics Target Data Type
biginttype	bigint
datetimetype	datetime
decimaltype(p,s), 1 <= p <= 38, 0 <= s <= 38	decimal(p,s), 1 <= p <= 38, 0 <= s <= 38
doubletype	float
filetype(1)	binary
filetype(precision), 100001 <= p <= 134217728	varbinary(max)
imagetype(1)	binary
imagetype(precision), 1000001 <= p <= 31457280	varbinary(max)
integertype	int
managedpropertytype(precision), 1 <= p <= 10485760	varchar(size), 4 <= s <= max
memotype(precision), 1 <= p <= 1048576	varchar(size), 4 <= s <= max
moneytype(p,s), 1 <= p <= 38, 0 <= s <= 38	decimal(p,s), 1 <= p <= 38, 0 <= s <= 38
picklisttype	int
statetype	int
statustype	int
stringtype(precision), 1 <= p <= 3901	varchar(size), 4 <= s <= max
uniqueidentifier(16)	uniqueidentifier

Microsoft Dynamics 365 Source and Microsoft Azure SQL Database Target

Microsoft Dynamics 365 Source Data Type	Microsoft Azure SQL Database Target Data Type
biginttype	bigint
booleantype	bit
datetimetype	datetime2(0)
decimaltype(p,s), 1 <= p <= 38, 0 <= s <= 38	decimal(p,s), 1 <= p <= 38, 0 <= s <= 38
doubletype	float
filetype(precision), 1 <= p <= 134217728	varbinary(max)
imagetype(precision), 1 <= p <= 31457280	varbinary(max)
integertype	int
managedpropertytype(precision), 1 <= p <= 10485760	varchar(size), 4 <= s <= max
memotype(precision), 1 <= p <= 1048576	varchar(size), 4 <= s <= max
moneytype(p,s), 1 <= p <= 38, 0 <= s <= 38	decimal(p,s), 1 <= p <= 38, 0 <= s <= 38
picklisttype	int
statetype	int
statustype	int
stringtype(precision), 1 <= p <= 3901	varchar(size), 4 <= s <= max
uniqueidentifier(16)	uniqueidentifier

Microsoft Dynamics 365 Source and Oracle Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Microsoft Dynamics 365 source and an Oracle target:

MSD365 Source Data Type	Oracle Target Data Type
biginttype	number(19)
datetimetype	date
decimaltype(p,s), 1 <= p <= 38, 0 <= s <= 38	number(p,s), 1 <= p <= 38, 0 <= s <= 38
doubletype	binary_double
filetype(precision), 1 <= p <= 134217728	blob
imagetype(precision), 1 <= p <= 31457280	blob
integertype	number(10)
managedpropertytype(precision), 1 <= p <= 1001	char(s char), 4 <= s <= 2000
managedpropertytype(precision), 2001 <= p <= 10485760	clob
memotype(precision), 1 <= p <= 1001	char(s char), 4 <= s <= 2000
memotype(precision), 2001 <= p <= 1048576	clob
moneytype(p,s), 1 <= p <= 38, 0 <= s <= 38	number(p,s), 1 <= p <= 38, 0 <= s <= 38
picklisttype	number(10)
statetype	number(10)
statustype	number(10)
stringtype(precision), 1 <= p <= 1901	char(s char), 4 <= s <= 2000
stringtype(precision), 2001 <= p <= 3901	clob
uniqueidentifier(16)	char(36 char)

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure an Oracle target.

Microsoft Dynamics 365 Source and Snowflake Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Microsoft Dynamics 365 source and a Snowflake target:

MSD365 Source Data Type	Snowflake Target Data Type
biginttype	number(19)
datetimetype	datetime(0)
decimaltype(38,38)	char(41)
decimaltype(p,s), 1 <= p <= 38, 0 <= s <= 37	number(p,s), 1 <= p <= 38, 0 <= s <= 37
doubletype	float
filetype(precision), 1 <= p <= 134217728	binary(size), 1 <= s <= 8300001
imagetype(precision), 1 <= p <= 31457280	binary(size), 1 <= s <= 8000001
integertype	number(10)
managedpropertytype(precision), 1 <= p <= 10485760	variant
memotype(precision), 1 <= p <= 1048576	char(size), 4 <= s <= 4194304
moneytype(38,38)	char(41)
moneytype(p,s), 1 <= p <= 38, 0 <= s <= 37	number(p,s), 1 <= p <= 38, 0 <= s <= 37
picklisttype	number(10)
statetype	number(10)
statustype	number(10)
stringtype(precision), 1 <= p <= 3901	char(size), 4 <= s <= 15604
uniqueidentifier(16)	char(36)

NetSuite Source and Amazon Redshift Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a NetSuite source and an Amazon Redshift target:

NetSuite Source Data Type	Amazon Redshift Target Data Type
bigint	bigint
char	character varying(4)
clob	binary varying(size), 262144 <= size <= 400000
clob	character varying(size), 4 <= size <= 65535
double(p,s), 1 <= p <= 38, 0 <= s <= 18	numeric(p,s), 1 <= p <= 38, 0 <= s <= 18
number	character varying(size), 40 <= size <= 41
number	numeric(p,s), 1 <= p <= 38, 0 <= s <= 16
timestamp	timestamp without time zone
varchar2	character varying(size), 4 <= size <= 65535

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure an Amazon S3 target.

NetSuite Source and Databricks Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a NetSuite source and a Databricks target:

NetSuite Source Data Type	Databricks Target Data Type
bigint	byte
bigint	integer
bigint	long
char	string
clob	string
double(p,s), 1 <= p <= 38, 0 <= s <= 18	decimal(p,s), 1 <= p <= 38, 1 <= s <= 18
number	decimal(p,s), 1 <= p <= 38, 0 <= s <= 16
number	string
timestamp	timestamp
varchar2	string

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure a Databricks target.

NetSuite Source and Google BigQuery Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a NetSuite source and a Google BigQuery target:

NetSuite Source Data Type	Google BigQuery Target Data Type
bigint	int64
char	string
clob	string
double(p,s), 1 <= p <= 38, 0 <= s <= 18	bignumeric
number	bignumeric
number	bignumeric
number	numeric
timestamp	datetime
varchar2	string

NetSuite Source and Microsoft Azure Synapse Analytics Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a NetSuite source and a Microsoft Azure Synapse Analytics target:

NetSuite Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
bigint	bigint
char	nchar
clob	char(8000)
clob	nchar(size), 1 <= size <= 4000
clob	nvarchar(max)
clob	nvarchar(max)
double(p,s), 1 <= p <= 38, 0 <= s <= 18	decimal(p,s), 1 <= p <= 38, 1 <= s <= 18
number	decimal(p,s), 1 <= p <= 38, 0 <= s <= 16
number	varchar(size), 40 <= size <= 41
timestamp	datetime
varchar2	varchar(size), 4 <= size <= max

NetSuite Source and Oracle Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a NetSuite source and an Oracle target:

NetSuite Source Data Type	Oracle Target Data Type
bigint	char(s char), 2 <= s <= 13
char	char(4 char)
clob	char(s char), 4 <= s <= 2000
clob	clob
double(p,s), 1 <= p <= 38, 0 <= s <= 18	number(p,s), 1 <= p <= 38, 1 <= s <= 18
number	char(s char), 40 <= s <= 41
number	number(p,s), 1 <= p <= 38, 0 <= s <= 16
timestamp	timestamp(1)
varchar2	char(s char), 4 <= s <= 2000
varchar2	clob

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure an Oracle target.

NetSuite Source and Snowflake Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a NetSuite source and a Snowflake target:

NetSuite Source Data Type	Snowflake Target Data Type
bigint	char(size), 2 <= size <= 13
char	char(4)
clob	char(size), 4 <= size <= 400000
double(p,0), 1 <= p <= 38	integer
double(p,s), 1 <= p <= 38, 1 <= s <= 18	number(p,s), 1 <= p <= 38, 1 <= s <= 18
number	number(p,s), 1 <= p <= 38, 0 <= s <= 16
number	varchar(size), 40 <= size <= 41
timestamp	datetime(1)
varchar2	varchar(size), 4 <= size <= 262136

Oracle Fusion Cloud source and Amazon Redshift target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with an Oracle Fusion Cloud source and Amazon Redshift target:

Oracle Fusion Cloud Source Data Type	Amazon Redshift Target Data Type
boolean	boolean
char(p), 1 <= p <= 2000	character varying(p), 4 <= p <= 8000
date	date
datetime	timestamp without time zone
datetime	timestamp without time zone
double	double precision
float	real
integer(p), 1 <= p <= 64	bigint
integer(p), 128 <= p <= 255	character varying(p), 40 <= p <= 78
integer(p), 65 <= p <= 127	numeric(p,0), 20 <= p <= 38
json	super
longvarchar(p), 1 <= p <= 2147483647	character varying(p), 4 <= p <= 65535
number(p,s), 2 <= p <= 38, 1 <= s <= 10	numeric(p,s), 2 <= p <= 38, 1 <= s <= 10
number(p,s), 2 <= p <= 38, 1 <= s <= 10	numeric(p,s), 2 <= p <= 38, 1 <= s <= 10
string(p), 1 <= p <= 2147483647	character varying(p), 4 <= p <= 65535
varchar(p), 1 <= p <= 2147483647	character varying(p), 4 <= p <= 65535

Oracle Fusion Cloud source and Databricks target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with an Oracle Fusion Cloud source and a Databricks target:

Oracle Fusion Cloud Source Data Type	Databricks Target Data Type
boolean	boolean
char(p), 1 <= p <= 2000	string
date	string
datetime	timestamp
datetime	timestamp
double	double
float	float
integer(p), 1 <= p <= 9	byte
integer(p), 10 <= p <= 32	integer
integer(p), 128 <= p <= 255	string
integer(p), 33 <= p <= 64	long
integer(p), 65 <= p <= 127	decimal(p), 20 <= p <= 38
longvarchar(p), 1 <= p <= 2147483647	string
number(p,s), 2 <= p <= 38, 1 <= s <= 10	decimal(p,s), 2 <= p <= 38, 1 <= s <= 10
number(p,s), 2 <= p <= 38, 1 <= s <= 10	decimal(p,s), 2 <= p <= 38, 1 <= s <= 10
string(p), 1 <= p <= 2147483647	string
varchar(p), 1 <= p <= 2147483647	string

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure a Databricks target.

Oracle Fusion Cloud source and Google BigQuery target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an Oracle Fusion Cloud source and Google BigQuery target:

Oracle Fusion Cloud Source Data Type	Google BigQuery Target Data Type
boolean	bool
char(p), 1 <= p <= 2000	string
date	date
datetime	datetime
datetime	datetime
double	float64
float	float64
integer(p), 1 <= p <= 64	int64
integer(p), 128 <= p <= 255	string
integer(p), 65 <= p <= 127	bignumeric
json	json
longvarchar(p), 1 <= p <= 2147483647	string
number(p,s), 2 <= p <= 38, 1 <= s <= 10	bignumeric
number(p,s), 2 <= p <= 38, 1 <= s <= 10	bignumeric
string(p), 1 <= p <= 2147483647	string
varchar(p), 1 <= p <= 2147483647	string

Oracle Fusion Cloud source and Oracle target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an Oracle Fusion Cloud source and Oracle target:

Oracle Fusion Cloud Source Data Type	Oracle Target Data Type
boolean	char(1 char)
char(p), 1 <= p <= 2000	char(s char), 4 <= s <= 2000
date	date
datetime	timestamp(3)
datetime	timestamp(3)
double	binary_double
float	binary_double
integer(1)	char(1 char)
integer(p), 128 <= p <= 255	char(s char), 40 <= s <= 78
integer(p), 2 <= p <= 127	number(p), 1 <= p <= 38
longvarchar(p), 1 <= p <= 2000	char(s char), 4 <= s <= 2000
longvarchar(p), 2001 <= p <= 2147483647	clob
number(p,s), 2 <= p <= 38, 1 <= s <= 10	number(p,s), 2 <= p <= 38, 1 <= s <= 10
number(p,s), 2 <= p <= 38, 1 <= s <= 10	number(p,s), 2 <= p <= 38, 1 <= s <= 10
string(p), 1 <= p <= 2000	char(s char), 4 <= s <= 2000
string(p), 2001 <= p <= 2147483647	clob
varchar(p), 1 <= p <= 2000	char(s char), 4 <= s <= 2000
varchar(p), 2001 <= p <= 2147483647	clob

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure an Oracle target.

Oracle Fusion Cloud source and Microsoft Azure Synapse Analytics target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an Oracle Fusion Cloud source and a Microsoft Azure Synapse Analytics target:

Oracle Fusion Cloud Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
boolean	bit
char(p), 1 <= p <= 2000	varchar(p), 4 <= p <= 8000
date	date
datetime	datetime
datetime	datetime
double	float
float	real
integer(p), 1 <= p <= 64	bigint
integer(p), 128 <= p <= 255	char(p), 40 <= p <= 78
integer(p), 65 <= p <= 127	decimal(p), 20 <= p <= 38
longvarchar(p), 1 <= p <= 2147483647	varchar(p), 4 <= p <= max
number(p,s), 2 <= p <= 38, 1 <= s <= 10	decimal(p,s), 2 <= p <= 38, 1 <= s <= 10
number(p,s), 2 <= p <= 38, 1 <= s <= 10	decimal(p,s), 2 <= p <= 38, 1 <= s <= 10
string(p), 1 <= p <= 2147483647	varchar(p), 4 <= p <= max
varchar(p), 1 <= p <= 2147483647	varchar(p), 4 <= p <= max

Oracle Fusion Cloud source and Snowflake target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an Oracle Fusion Cloud source and Snowflake target:

Oracle Fusion Cloud Source Data Type	Snowflake Target Data Type
boolean	boolean
char(p), 1 <= p <= 2000	varchar(p), 4 <= p <= 8000
date	date
datetime	datetime(3)
datetime	datetime(3)
double	float
float	float
integer(1)	char
integer(p), 128 <= p <= 255	char(p), 40 <= p <= 78
integer(p), 2 <= p <= 127	integer
json	variant
longvarchar(p), 1 <= p <= 2147483647	varchar(p), 4 <= p <= 127996
number(p,s), 2 <= p <= 38, 1 <= s <= 10	number(p,s), 2 <= p <= 38, 1 <= s <= 10
number(p,s), 2 <= p <= 38, 1 <= s <= 10	number(p,s), 2 <= p <= 38, 1 <= s <= 10
string(p), 1 <= p <= 2147483647	varchar(p), 4 <= p <= 127996
varchar(p), 1 <= p <= 2147483647	varchar(p), 4 <= p <= 127996

Salesforce Source and Amazon Redshift Target

The following table identifies the default data-type mappings for Application Ingestion and Replication configurations with a Salesforce source and an Amazon Redshift target:

Salesforce Source Data Type	Amazon Redshift Target Data Type
anytype(precision), 1 <= p <= 255	character varying(size), 1 <= size <= 255
base64 Note: The precision depends on the base64 body size you select.	character varying(size), 1 <= size <= 65535
boolean	boolean
combobox(precision), 1 <= p <= 255	character varying(size), 1 <= size <= 255
currency(p,s), 1 <= p <= 18, 0 <= s <= 17	numeric(p,s), 1 <= p <= 18, 0 <= s <= 17
date	date
datetime	timestamp without time zone
double(p,s), 1 <= p <= 18, 0 <= s <= 17	numeric(p,s), 1 <= p <= 18, 0 <= s <= 17
email(precision), 1 <= p <= 80	character varying(size), 1 <= size <= 80
encryptedstring(precision), 1 <= p <= 175	character varying(size), 1 <= size <= 175
id(precision), 1 <= p <= 18	character varying(size), 1 <= size <= 18
int	integer
long	bigint
multipicklist(precision), 1 <= p <= 4099	character varying(size), 1 <= size<= 4099
percent(p,s), 1 <= p <= 18, 0 <= s <= 17	numeric(p,s), 1 <= p <= 18, 0 <= s <= 17
phone(precision), 1 <= p <= 40	character varying(size), 1 <= size <= 40
picklist(precision), 1 <= p <= 255	character varying(size), 1 <= size <= 255
reference(precision), 1 <= p <= 18	character varying(size), 1 <= size <= 18
string(precision), 1 <= p <= 100	character varying(size), 1 <= size <= 100
textarea(precision), 1 <= p <= 131072	character varying(size), 1 <= size <= 65535
time	time without time zone
url(precision), 1 <= p <= 255	character varying(size), 1 <= size <= 255

Salesforce Source and Databricks Target

The following table identifies the default data-type mappings for Application Ingestion and Replication configurations with a Salesforce source and a Databricks target:

Salesforce Source Data Type	Databricks Target Data Type
anytype(precision), 1 <= p <= 255	string
base64 Note: The precision depends on the base64 body size you select.	string
boolean	boolean
combobox(precision), 1 <= p <= 255	string
currency(p,s), 1 <= p <= 18, 0 <= s <= 17	decimal(p,s), 1 <= p <= 18, 1 <= s <= 17
date	string
datetime	timestamp
double(p,s), 1 <= p <= 18, 0 <= s <= 17	decimal(p,s), 1 <= p <= 18, 1 <= s <= 17
email(precision), 1 <= p <= 80	string
encryptedstring(precision), 1 <= p <= 175	string
id(precision), 1 <= p <= 18	string
int	integer
long	long
multipicklist(precision), 1 <= p <= 4099	string
percent(p,s), 1 <= p <= 18, 0 <= s <= 17	decimal(p,s), 1 <= p <= 18, 1 <= s <= 17
phone(precision), 1 <= p <= 40	string
picklist(precision), 1 <= p <= 255	string
reference(precision), 1 <= p <= 18	string
string(precision), 1 <= p <= 100	string
textarea(precision), 1 <= p <=131072	string
time	string
url(precision), 1 <= p <= 255	string

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure a Databricks target.

Salesforce Source and Google BigQuery Target

The following table identifies the default data-type mappings for Application Ingestion and Replication configurations with a Salesforce source and a Google BigQuery target:

Salesforce Source Data Type	Google BigQuery Target Data Type
anytype(precision), 1 <= p <= 255	string
base64 Note: The precision depends on the base64 body size you select.	string
boolean	bool
combobox(precision), 1 <= p <= 255	string
currency(p,0), 1 <= p <= 18	numeric
currency(p,s), 1 <= p <= 18, 1 <= s <= 9	numeric
currency(p,s), 1 <= p <= 18, 10 <= s <= 17	bignumeric
date	date
datetime	datetime
double(p,0), 1 <= p <= 18	numeric
double(p,s), 1 <= p <= 18, 1 <= s <= 9	numeric
double(p,s), 1 <= p <= 18, 10 <= s <= 17	bignumeric
email(precision), 1 <= p <= 80	string
encryptedstring(precision), 1 <= p <= 175	string
id(precision), 1 <= p <= 18	string
int	int64
long	int64
multipicklist(precision), 1 <= p <= 4099	string
percent(p,0), 1 <= p <= 18	numeric
percent(p,s), 1 <= p <= 18, 1 <= s <= 9	numeric
percent(p,s), 1 <= p <= 18, 10 <= s <= 17	bignumeric
phone(precision), 1 <= p <= 40	string
picklist(precision), 1 <= p <= 255	string
reference(precision), 1 <= p <= 18	string
string(precision), 1 <= p <= 100	string
textarea(precision), 1 <= p <=131072	string
time	time
url(precision), 1 <= p <= 255	string

Salesforce Source and Microsoft Azure Synapse Analytics Target

The following table identifies the default data-type mappings for Application Ingestion and Replication configurations with a Salesforce source and a Microsoft Azure Synapse Analytics target:

Salesforce Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
anytype(precision), 1 <= p <= 255	varchar(size), 1 <= size <= 255
base64 Note: The precision depends on the base64 body size you select.	nchar(size), 1 <= size <= 255
boolean	bit
combobox(precision), 1 <= p <= 255	varchar(size), 1 <= size <= 255
currency(p,s), 1 <= p <= 18, 0 <= s <= 17	decimal(p,s), 1 <= p <= 18, 1 <= s <= 17
date	date
datetime	datetime2(3)
double(p,s), 1 <= p <= 18, 0 <= s <= 17	decimal(p,s), 1 <= p <= 18, 1 <= s <= 17
email(precision), 1 <= p <= 80	varchar(size), 1 <= size <= 80
encryptedstring(precision), 1 <= p <= 175	varchar(size), 1 <= size <= 175
id(precision), 1 <= p <= 18	varchar(size), 1 <= size <= 18
int	int
long	bigint
multipicklist(precision), 1 <= p <= 4099	varchar(size), 1 <= size <= 4099
percent(p,s), 1 <= p <= 18, 0 <= s <= 17	decimal(p,s), 1 <= p <= 18, 1 <= s <= 17
phone(precision), 1 <= p <= 40	varchar(size), 1 <= size <= 40
picklist(precision), 1 <= p <= 255	varchar(size), 1 <= size <= 255
reference(precision), 1 <= p <= 18	varchar(size), 1 <= size <= 18
string(precision), 1 <= p <= 100	varchar(size), 1 <= size <= 100
textarea(precision), 1 <= p <=131072	varchar(size), 1 <= size <= max
time	time(3)
url(precision), 1 <= p <= 255	varchar(size), 1 <= size <= 255

Salesforce Source and Microsoft Azure SQL Database Target

The following table identifies the default data-type mappings for Application Ingestion and Replication configurations with a Salesforce source and Microsoft Azure SQL Database target:

Salesforce Source Data Type	Microsoft Azure SQL Database Target Data Type
anytype(precision), 1 <= p <= 255	character varying(size), 1 <= size <= 255
base64 Note: The precision depends on the base64 body size you select.	character varying(size), 1 <= size <= max
boolean	bit
combobox(precision), 1 <= p <= 255	character varying(size), 1 <= size <= 255
currency(p,s), 1 <= p <= 18, 0 <= s <= 17	decimal(p,s), 1 <= p <= 18, 1 <= s <= 17
date	date
datetime	datetime2 (3)
double(p,s), 1 <= p <= 18, 0 <= s <= 17	decimal(p,s), 1 <= p <= 18, 1 <= s <= 17
email(precision), 1 <= p <= 80	character varying(size), 1 <= size <= 80
encryptedstring(precision), 1 <= p <= 175	character varying(size), 1 <= size <= 175
id(precision), 1 <= p <= 18	character varying(size), 1 <= size <= 18
int	int
long	long
multipicklist(precision), 1 <= p <= 4099	character varying(size), 1 <= size <= 4099
percent(p,s), 1 <= p <= 18, 0 <= s <= 17	decimal(p,s), 1 <= p <= 18, 1 <= s <= 17
phone(precision), 1 <= p <= 40	character varying(size), 1 <= size <= 40
picklist(precision), 1 <= p <= 255	character varying(size), 1 <= size <= 255
reference(precision), 1 <= p <= 18	character varying(size), 1 <= size <= 18
string(precision), 1 <= p <= 100	character varying(size), 1 <= size <= 100
textarea(precision), 1 <= p <= 131072	character varying(size), 1 <= size <= 131072
time	time(precision) without time zone, 3 <= p <= null
url(precision), 1 <= p <= 255	character varying(size), 1 <= size <= 255

Salesforce Source and Oracle Target

The following table identifies the default data-type mappings for Application Ingestion and Replication configurations with a Salesforce source and an Oracle target:

Salesforce Source Data Type	Oracle Target Data Type
anytype(precision), 1 <= p <= 255	char(s char), 1 <= s <= 255
base64 Note: The precision depends on the base64 body size you select.	clob
boolean	char(1 char)
combobox(precision), 1 <= p <= 255	char(s char), 1 <= s <= 255
currency(p,s), 1 <= p <= 18, 0 <= s <= 17	number(p,s), 1 <= p <= 18, 1 <= s <= 17
date	date
datetime	timestamp(3)
double(p,s), 1 <= p <= 18, 0 <= s <= 17	number(p,s), 1 <= p <= 18, 1 <= s <= 17
email(precision), 1 <= p <= 80	char(s char), 1<= s <= 80
encryptedstring(precision), 1 <= p <= 175	char(s char), 1 <= s <= 175
id(precision), 1 <= p <= 18	char(s char), 1 <= s <= 18
int	number(10)
long	number(19)
multipicklist(precision),1 <= p <= 4099	clob
percent(p,s), 1 <= p <= 18, 0 <= s <= 17	number(p,s), 1 <= p <= 18, 1 <= s <= 17
phone(precision), 1 <= p <= 40	char(s char), 1 <= s <= 40
picklist(precision), 1 <= p <= 255	char(s char), 1 <= s <= 255
reference(precision), 1 <= p <= 18	char(s char), 1 <= s <= 18
string(precision), 1 <= p <= 100	char(s char), 1 <= s <= 100
textarea(precision), 1 <= p <= 4000	char(s char), 1 <= s <= 4000
textarea(precision), 4001 <= p <= 131072	clob
time	timestamp(3)
url(precision), 1 <= p <= 255	char(s char), 1<= s <= 255

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure an Oracle target.

Salesforce Source and PostgreSQL Target

The following table identifies the default data-type mappings for Application Ingestion and Replication configurations with a Salesforce source and a PostgreSQL target:

Salesforce Source Data Type	PostgreSQL Target Data Type
anytype(precision), 1 <= p <= 255	character varying(size), 1 <= size <= 255
base64 Note: The precision depends on the base64 body size you select.	character varying(size), 1 <= size <= max
boolean	boolean
combobox(precision), 1 <= p <= 255	character varying(size), 1 <= size <= 255
currency(p,s), 1 <= p <= 18, 0 <= s <= 17	numeric(p,s), 1 <= p <= 18, 1 <= s <= 17
date	date
datetime	timestamp(precision) without time zone, 3 <= p <= null
double(p,s), 1 <= p <= 18, 0 <= s <= 17	numeric(p,s), 1 <= p <= 18, 1 <= s <= 17
email(precision), 1 <= p <= 80	character varying(size), 1 <= size <= 80
encryptedstring(precision), 1 <= p <= 175	character varying(size), 1 <= size <= 175
id(precision), 1 <= p <= 18	character varying(size), 1 <= size <= 18
int	integer
long	bigint
multipicklist(precision), 1 <= p <= 4099	character varying(size), 1 <= size <= 4099
percent(p,s), 1 <= p <= 18, 0 <= s <= 17	numeric(p,s), 1 <= p <= 18, 1 <= s <= 17
phone(precision), 1 <= p <= 40	character varying(size), 1 <= size <= 40
picklist(precision), 1 <= p <= 255	character varying(size), 1 <= size <= 255
reference(precision), 1 <= p <= 18	character varying(size), 1 <= size <= 18
string(precision), 1 <= p <= 100	character varying(size), 1 <= size <= 100
textarea(precision), 1 <= p <= 131072	character varying(size), 1 <= size <= 131072
time	time(precision) without time zone, 3 <= p <= null
url(precision), 1 <= p <= 255	character varying(size), 1 <= size <= 255

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure a PostgreSQL target.

Salesforce Source and Snowflake Target

The following table identifies the default data-type mappings for Application Ingestion and Replication configurations with a Salesforce source and a Snowflake target:

Salesforce Source Data Type	Snowflake Target Data Type
anytype(precision), 1 <= p <= 255	char(size), 4 <= size <= 1020
base64 Note: The precision depends on the base64 body size you select.	char(size), 4 <= size <= 1020
boolean	boolean
combobox(precision), 1 <= p <= 255	char(size), 4 <= size <= 1020
currency(p,0), 1 <= p <= 18	integer
currency(p,s), 1 <= p <= 18, 1 <= s <= 17	number(p,s), 1 <= p <= 18, 1 <= s <= 17
date	date
datetime	datetime(3)
double(p,0), 1 <= p <= 18	integer
double(p,s), 1 <= p <= 18, 1 <= s <= 17	number(p,s), 1 <= p <= 18, 1 <= s <= 17
email(precision), 1 <= p <= 80	char(size), 4 <= size <= 320
encryptedstring(precision), 1 <= p <= 175	char(size), 4 <= size <= 700
id(precision), 1 <= p <= 18	char(size), 4 <= size <= 72
int	number(10)
long	number(19)
multipicklist(precision), 1 <= p <= 4099	char(size), 4 <= size <= 16396
percent(p,0), 1 <= p <= 18	integer
percent(p,s), 1 <= p <= 18, 1 <= s <= 17	number(p,s), 1 <= p <= 18, 1 <= s <= 17
phone(precision), 1 <= p <= 40	char(size), 4 <= size <= 160
picklist(precision), 1 <= p <= 255	char(size), 4 <= size <= 1020
reference(precision), 1 <= p <= 18	char(size), 4 <= size <= 72
string(precision), 1 <= p <= 100	char(size), 4 <= size <= 400
textarea(precision), 1 <= p <= 131072	char(size), 4 <= size <= 131072
time	time(3)
url(precision), 1 <= p <= 255	char(size), 4 <= size <= 1020

Salesforce Marketing Cloud Source and Amazon Redshift Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Salesforce Marketing Cloud source and an Amazon Redshift target:

Salesforce Marketing Cloud Source Data Type	Amazon Redshift Target Data Type
boolean	boolean
date(0)	timestamp without time zone
decimal(p,s), 1 <= p <= 29, 0 <= s <= 8	numeric(p,s), 1 <= p <= 29, 0 <= s <= 8
emailaddress(precision), 1 <= p <= 254	character varying(size), 4 <= size <= 1016
locale(precision), 1 <= p <= 5	character varying(size), 4 <= size <= 20
number	integer
phone(precision), 1 <= p <= 50	character varying(size), 4 <= size <= 200
text(precision), 1 <= p <= 4000	character varying(size), 4 <= size <= 16000

Salesforce Marketing Cloud Source and Databricks Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Salesforce Marketing Cloud source and a Databricks target:

Salesforce Marketing Cloud Source Data Type	Databricks Target Data Type
boolean	boolean
date(0)	timestamp
decimal(p,s), 1 <= p <= 29, 0 <= s <= 8	decimal(p,s), 1 <= p <= 29, 1 <= s <= 8
emailaddress(precision), 1 <= p <= 254	string
locale(precision), 1 <= p <= 5	string
number	integer
phone(precision), 1 <= p <= 50	string
text(precision), 1 <= p <= 4000	string

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure a Databricks target.

Salesforce Marketing Cloud Source and Google BigQuery Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Salesforce Marketing Cloud source and a Google BigQuery target:

Salesforce Marketing Cloud Source Data Type	Google BigQuery Target Data Type
boolean	bool
date(0)	datetime
decimal(p,s), 1 <= p <= 29, 0 <= s <= 8	bignumeric
emailaddress(precision), 1 <= p <= 254	string
locale(precision), 1 <= p <= 5	string
number	int64
phone(precision), 1 <= p <= 50	string
text(precision), 1 <= p <= 4000	string

Salesforce Marketing Cloud Source and Microsoft Azure Synapse Analytics Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Salesforce Marketing Cloud source and a Microsoft Azure Synapse Analytics target:

Salesforce Marketing Cloud Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
boolean	bit
date(0)	datetime
decimal(p,s), 1 <= p <= 29, 0 <= s <= 8	decimal(p,s), 1 <= p <= 29, 1 <= s <= 8
emailaddress(precision), 1 <= p <= 254	nchar(size), 1 <= size <= 254
locale(precision), 1 <= p <= 5	nchar(size), 1 <= size <= 5
number	int
phone(precision), 1 <= p <= 50	nchar(size), 1 <= size <= 50
text(precision), 1 <= p <= 4000	nchar(size), 1 <= size <= 4000

Salesforce Marketing Cloud Source and Oracle Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Salesforce Marketing Cloud source and an Oracle target:

Salesforce Marketing Cloud Source Data Type	Oracle Target Data Type
boolean	char(1 char)
date(0)	date
decimal(p,s), 1 <= p <= 29, 0 <= s <= 8	number(p,s), 1 <= p <= 29, 1 <= s <= 8
emailaddress(precision), 1 <= p <= 254	char(s char), 4 <= s <= 1016
locale(precision), 1 <= p <= 5	char(s char), 4 <= s <= 20
number	number(10)
phone(precision), 1 <= p <= 50	char(s char), 4 <= s <= 200
text(precision), 1 <= p <= 2000	char(s char), 4 <= s <= 2000
text(precision), 2001 <= p <= 4000	clob

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure an Oracle target.

Salesforce Marketing Cloud Source and Snowflake Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a Salesforce Marketing Cloud source and a Snowflake target:

Salesforce Marketing Cloud Source Data Type	Snowflake Target Data Type
boolean	boolean
date(0)	datetime(0)
decimal(p,0), 1 <= p <= 29	integer
decimal(p,s), 1 <= p <= 29, 1 <= s <= 8	number(p,s), 1 <= p <= 29, 1 <= s <= 8
emailaddress(precision), 1 <= p <= 254	char(size), 4 <= size <= 1016
locale(precision), 1 <= p <= 5	char(size), 4 <= size <= 20
number	number(10)
phone(precision), 1 <= p <= 50	char(size), 4 <= size <= 200
text(precision), 1 <= p <= 4000	char(size), 4 <= size <= 16000

SAP Source and Amazon Redshift Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP source and an Amazon Redshift target:

SAP Source Data Type	Amazon Redshift Target Data Type
d16r	double precision
d34r	double precision
fltp	double precision
int1	smallint
int2	smallint
int4	integer
int8	bigint

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•D16S
•D34S
•PREC
•VARC

Additionally, application ingestion and replication jobs do not support the RSTR data type.

SAP Source and Databricks Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP source and a Databricks target:

SAP Source Data Type	Databricks Target Data Type
d16r	double
d34r	double
fltp	double
int1	integer
int2	integer
int4	integer
int8	long

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•D16S
•D34S
•PREC
•VARC

Additionally, application ingestion and replication jobs do not support the RSTR data type.

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure a Databricks target.

SAP Source and Google BigQuery Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP source and a Google BigQuery target:

SAP Source Data Type	Google BigQuery Target Data Type
d16r	float64
d34r	float64
fltp	float64
int1	int64
int2	int64
int4	int64
int8	int64

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•D16S
•D34S
•PREC
•VARC

Additionally, application ingestion and replication jobs do not support the RSTR data type.

SAP Source and Microsoft Azure Synapse Analytics Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP source and a Microsoft Azure Synapse Analytics target:

SAP Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
d16r	float
d34r	float
fltp	float
int1	tinyint
int2	smallint
int4	int
int8	bigint

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•D16S
•D34S
•PREC
•VARC

Additionally, application ingestion and replication jobs do not support the RSTR data type.

SAP Source and Oracle Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with an SAP source and an Oracle target:

SAP Source Data Type	Oracle Target Data Type
CHAR	VARCHAR2(20)
ACCP	VARCHAR2(24)
CURR	NUMBER(31,8)
CUKY	VARCHAR2(20)
DF16_DEC	BINARY_DOUBLE
DF16_RAW	BINARY_DOUBLE
DF34_DEC	BINARY_DOUBLE
DF34_RAW	BINARY_DOUBLE
DEC	NUMBER(31,9)
DATS	DATE
CLNT	VARCHAR2(12)
INT2	NUMBER(5,0)
LANG	VARCHAR2(4)
NUMC	VARCHAR2(40)
RAW	BLOB
SSTRING	CLOB
STRING	CLOB
TIMS	TIMESTAMP
QUAN	NUMBER(31,6)
UNIT	VARCHAR2(12)
INT1	NUMBER(3,0)
INT4	NUMBER(10,0)
LCHR	VARCHAR2(2000)

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•D16S
•D34S
•PREC
•VARC

Additionally, application ingestion and replication jobs do not support the RSTR data type.

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure an Oracle target.

SAP Source and Snowflake Target

The following table identifies the recommended data-type mappings for Application Ingestion and Replication configurations with a SAP source and a Snowflake target:

SAP Source Data Type	Snowflake Target Data Type
d16r	float
d34r	float
fltp	float
int1	number(3)
int2	number(5)
int4	number(10)
int8	number(19)

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•D16S
•D34S
•PREC
•VARC

Additionally, application ingestion and replication jobs do not support the RSTR data type.

SAP Mass Ingestion connection Source and Amazon Redshift Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP Mass Ingestion connection source and an Amazon Redshift target:

SAP Mass Ingestion connection Source Data Type	Amazon Redshift Target Data Type
accp(6)	character varying(24)
char(p), 1 <= p <= 255	character varying(p), 4 <= p <= 1020
clnt(p), 1 <= p <= 3	character varying(p), 4 <= p <= 12
cuky(p), 1 <= p <= 5	character varying(p), 4 <= p <= 20
curr(p,s), 1 <= p <= 38, 0 <= s <= 16	numeric(p,s), 1 <= p <= 38, 0 <= s <= 16
d16d(p,s), 1 <= p <= 38, 0 <= s <= 16	numeric(p,s), 1 <= p <= 38, 0 <= s <= 16
d16r	double precision
d34d(p,s), 1 <= p <= 38, 0 <= s <= 16	numeric(p,s), 1 <= p <= 38, 0 <= s <= 16
d34r	double precision
dats	date
dec(p,s), 1 <= p <= 38, 0 <= s <= 16	numeric(p,s), 1 <= p <= 38, 0 <= s <= 16
fltp	double precision
int1	smallint
int2	smallint
int4	integer
int8	bigint
lang(1)	character varying(4)
lchr *	character varying (65535)
lraw *	binary varying(1024000)
numc(p), 1 <= p <= 255	character varying(p), 4 <= p <= 1020
quan(p,s), 1 <= p <= 38, 0 <= s <= 16	numeric(p,s), 1 <= p <= 38, 0 <= s <= 16
raw(p), 1 <= p <= 255	binary varying(p), 1 <= p <= 255
sstr(p), 1 <= p <= 1333	character varying(p), 4 <= p <= 5332
strg *	character varying (65535)
tims	time without time zone
unit(p), 1 <= p <= 5	character varying(p), 4 <= p <= 20
* SAP doesn't specify the maximum length for these data types.

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•d16s
•d34s
•prec
•varc

Additionally, application ingestion and replication jobs do not support the rstr data type.

SAP Mass Ingestion connection Source and Databricks Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP Mass Ingestion connection source and a Microsoft Azure Synapse Analytics target:

SAP Mass Ingestion connection Source Data Type	Databricks Target Data Type
accp(6)	string
char(p), 1 <= p <= 255	string
clnt(p), 1 <= p <= 3	string
cuky(p), 1 <= p <= 5	string
curr(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
d16d(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
d16r	double
d34d(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
d34r	double
dats	string
dec(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
fltp	double
int1	integer
int2	integer
int4	integer
int8	long
lang(1)	string
lchr *	string
lraw *	binary
numc(p), 1 <= p <= 255	string
quan(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
raw(p), 1 <= p <= 255	binary
sstr(p), 1 <= p <= 1333	string
strg *	string
tims	string
unit(p), 1 <= p <= 5	string
* SAP doesn't specify the maximum length for these data types.

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•d16s
•d34s
•prec
•varc

Additionally, application ingestion and replication jobs do not support the rstr data type.

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure a Databricks target.

SAP Mass Ingestion connection Source and Google BigQuery Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP Mass Ingestion connection source and a Google BigQuery target:

SAP Mass Ingestion connection Source Data Type	Google BigQuery Target Data Type
accp(6)	string
char(p), 1 <= p <= 255	string
clnt(p), 1 <= p <= 3	string
cuky(p), 1 <= p <= 5	string
curr(p,s), 1 <= p <= 38, 0 <= s <= 16	bignumeric
d16d(p,s), 1 <= p <= 38, 0 <= s <= 16	bignumeric
d16r	float64
dats	date
dec(p,s), 1 <= p <= 38, 0 <= s <= 16	bignumeric
fltp	float64
int1	int64
int2	int64
int4	int64
int8	int64
lang(1)	string
lchr *	string
lraw *	bytes
numc(p), 1 <= p <= 255	string
quan(p,s), 1 <= p <= 38, 0 <= s <= 16	bignumeric
raw(p), 1 <= p <= 255	bytes
sstr(p), 1 <= p <= 1333	string
strg *	string
tims	time
unit(p), 1 <= p <= 5	string
* SAP doesn't specify the maximum length for these data types.

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•d16s
•d34s
•prec
•varc

Additionally, application ingestion and replication jobs do not support the rstr data type.

SAP Mass Ingestion connection source and Microsoft Azure Synapse Analytics Target

SAP Mass Ingestion connection Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
accp(6)	varchar(24)
char(1)	nchar null
char(p), 2 <= p <= 255	nchar(p), 2 <= p <= 255
clnt(1)	nchar null
clnt(p), 2 <= p <= 3	nchar(p), 2 <= p <= 3
cuky(1)	nchar null
cuky(p), 2 <= p <= 5	nchar(p), 2 <= p <= 5
curr(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
d16d(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
d16r	float
d34d(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
d34r	float
dats	date
dec(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
fltp	float
int1	bigint
int2	bigint
int4	bigint
int8	bigint
lang(1)	nchar null
lchr *	varchar(max)
lraw *	varbinary(max)
numc(1)	nchar null
numc(p), 2 <= p <= 255	nchar(p), 2 <= p <= 255
quan(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
raw(1)	binary null
raw(p), 2 <= p <= 255	binary(p), 2 <= p <= 255
sstr(1)	nchar null
sstr(p), 2 <= p <= 1333	nchar(p), 2 <= p <= 1333
strg *	char null
tims	time(0)
unit(1)	nchar null
unit(p), 2 <= p <= 5	nchar(p), 2 <= p <= 5
* SAP doesn't specify the maximum length for these data types.

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•d16s
•d34s
•prec
•varc

Additionally, application ingestion and replication jobs do not support the rstr data type.

SAP Mass Ingestion connection Source and Oracle Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP Mass Ingestion source and an Oracle target:

SAP Mass Ingestion Source Data Type	Oracle Target Data Type
accp(6)	varchar2(24 char)
char(p), 1 <= p <= 255	varchar2(s char), 4 <= s <= 1020
clnt(p), 1 <= p <= 3	varchar2(s char), 4 <= s <= 12
cuky(p), 1 <= p <= 5	varchar2(s char), 4 <= s <= 20
curr(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
d16d(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
d16r	binary_double
d34d(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
d34r	binary_double
dats	date
dec(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
fltp	binary_double
int1	number(3)
int2	number(5)
int4	number(10)
int8	number(19)
lang(1)	varchar2(4 char)
lchr *	varchar2(1 char)
lraw *	blob null
numc(p), 1 <= p <= 255	varchar2(s char), 4 <= s <= 1020
quan(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
raw(p), 1 <= p <= 255	blob null
sstr(p), 1 <= p <= 1333	varchar2(s char), 4 <= s <= 4000
strg *	varchar2(1 char)
tims	timestamp(0)
unit(p), 1 <= p <= 5	varchar2(s char), 4 <= s <= 20
* SAP doesn't specify the maximum length for these data types.

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•d16s
•d34s
•prec
•varc

Additionally, application ingestion and replication jobs do not support the rstr data type.

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure an Oracle target.

SAP Mass Ingestion connection Source and Snowflake Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP Mass Ingestion connection source and a Snowflake target:

SAP Mass Ingestion connection Source Data Type	Snowflake Target Data Type
accp(6)	varchar(24)
char(p), 1 <= p <= 255	varchar(p), 4 <= p <= 1020
clnt(p), 1 <= p <= 3	varchar(p), 4 <= p <= 12
cuky(p), 1 <= p <= 5	varchar(p), 4 <= p <= 20
curr(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
d16d(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
d16r	float
d34d(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
d34r	float
dats	date
dec(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
fltp	float
int1	number(3)
int2	number(5)
int4	number(10)
int8	number(19)
lang(1)	varchar(4)
lchr *	varchar(4)
lraw *	binary(1)
numc(p), 1 <= p <= 255	varchar(p), 4 <= p <= 1020
quan(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
raw(p), 1 <= p <= 255	binary(p), 1 <= p <= 255
sstr(p), 1 <= p <= 1333	varchar(p), 4 <= p <= 5332
strg *	varchar(4)
tims	time(0)
unit(p), 1 <= p <= 5	varchar(p), 4 <= p <= 20
* SAP doesn't specify the maximum length for these data types.

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•d16s
•d34s
•prec
•varc

Additionally, application ingestion and replication jobs do not support the rstr data type.

SAP ODP Source and Amazon Redshift Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP ODP source and an Amazon Redshift target:

SAP ODP Source Data Type	Amazon Redshift Target Data Type
accp(6)	character varying(24)
char(p), 1 <= p <= 255	character varying(p), 4 <= p <= 1020
clnt(p), 1 <= p <= 3	character varying(p), 4 <= p <= 12
cuky(p), 1 <= p <= 5	character varying(p), 4 <= p <= 20
curr(p,s), 1 <= p <= 38, 0 <= s <= 16	numeric(p,s), 1 <= p <= 38, 0 <= s <= 16
d16d(p,s), 1 <= p <= 38, 0 <= s <= 16	numeric(p,s), 1 <= p <= 38, 0 <= s <= 16
d16r	double precision
d34d(p,s), 1 <= p <= 38, 0 <= s <= 16	numeric(p,s), 1 <= p <= 38, 0 <= s <= 16
d34r	double precision
dats	date
dec(p,s), 1 <= p <= 38, 0 <= s <= 16	numeric(p,s), 1 <= p <= 38, 0 <= s <= 16
fltp	double precision
int1	smallint
int2	smallint
int4	integer
int8	bigint
lang(1)	character varying(4)
lchr *	character varying (65535)
lraw *	binary varying (1024000)
numc(p), 1 <= p <= 255	character varying(p), 4 <= p <= 1020
quan(p,s), 1 <= p <= 38, 0 <= s <= 16	numeric(p,s), 1 <= p <= 38, 0 <= s <= 16
raw(p), 1 <= p <= 255	binary varying(p), 1 <= p <= 255
sstr(p), 1 <= p <= 1333	character varying(p), 4 <= p <= 5332
strg *	character varying (65535)
tims	time without time zone
unit(p), 1 <= p <= 5	character varying(p), 4 <= p <= 20
* SAP doesn't specify the maximum length for these data types.

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•d16s
•d34s
•prec
•varc

Additionally, application ingestion and replication jobs do not support the rstr data type.

SAP ODP Source and Databricks Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP ODP source and a Databricks target:

SAP ODP Source Data Type	Databricks Target Data Type
accp(6)	string
char(p), 1 <= p <= 255	string
clnt(p), 1 <= p <= 3	string
cuky(p), 1 <= p <= 5	string
curr(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
d16d(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
d16r	double
d34d(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
d34r	double
dats	string
dec(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
fltp	double
int1	integer
int2	integer
int4	integer
int8	long
lang(1)	string
lchr *	string
lraw *	binary
numc(p), 1 <= p <= 255	string
quan(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
raw(p), 1 <= p <= 255	binary
sstr(p), 1 <= p <= 1333	string
strg *	string
tims	string
unit(p), 1 <= p <= 5	string
* SAP doesn't specify the maximum length for these data types.

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•d16s
•d34s
•prec
•varc

Additionally, application ingestion and replication jobs do not support the rstr data type.

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure a Databricks target.

SAP ODP Source and Google BigQuery Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP Mass Ingestion connection source and a Google BigQuery target:

SAP Mass Ingestion connection Source Data Type	Google BigQuery Target Data Type
accp(6)	string
char(p), 1 <= p <= 255	string
clnt(p), 1 <= p <= 3	string
cuky(p), 1 <= p <= 5	string
curr(p,s), 1 <= p <= 38, 0 <= s <= 16	bignumeric
d16d(p,s), 1 <= p <= 38, 0 <= s <= 16	bignumeric
d16r	float64
dats	date
dec(p,s), 1 <= p <= 38, 0 <= s <= 16	bignumeric
fltp	float64
int1	int64
int2	int64
int4	int64
int8	int64
lang(1)	string
lchr *	string
lraw *	string
numc(p), 1 <= p <= 255	string
quan(p,s), 1 <= p <= 38, 0 <= s <= 16	bignumeric
raw(p), 1 <= p <= 255	bytes
sstr(p), 1 <= p <= 1333	string
strg *	string
tims	time
unit(p), 1 <= p <= 5	string
* SAP doesn't specify the maximum length for these data types.

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•d16s
•d34s
•prec
•varc

Additionally, application ingestion and replication jobs do not support the rstr data type.

SAP ODP Source and Microsoft Azure Synapse Analytics Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP ODP source and a Microsoft Azure Synapse Analytics target:

SAP ODP Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
accp(6)	varchar(24)
char(p), 1 <= p <= 255	varchar(p), 4 <= p <= 1020
clnt(p), 1 <= p <= 3	varchar(p), 4 <= p <= 12
cuky(p), 1 <= p <= 5	varchar(p), 4 <= p <= 20
curr(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
d16d(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
d16r	float
d34d(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
d34r	float
dats	date
dec(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
fltp	float
int1	tinyint
int2	smallint
int4	int
int8	bigint
lang(1)	varchar(4)
lchr *	varchar(max)
lraw *	varbinary(max)
numc(p), 1 <= p <= 255	varchar(p), 4 <= p <= 1020
quan(p,s), 1 <= p <= 38, 0 <= s <= 16	decimal(p,s), 1 <= p <= 38, 1 <= s <= 16
raw(1)	binary null
raw(p), 2 <= p <= 255	binary(p), 2 <= p <= 255
sstr(p), 1 <= p <= 1333	varchar(p), 4 <= p <= 5332
strg *	varchar null
tims	time(0)
unit(p), 1 <= p <= 5	varchar(p), 4 <= p <= 20
* SAP doesn't specify the maximum length for these data types.

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•d16s
•d34s
•prec
•varc

Additionally, application ingestion and replication jobs do not support the rstr data type.

SAP ODP Source and Oracle Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP ODP source and an Oracle target:

SAP ODP Source Data Type	Oracle Target Data Type
accp(6)	varchar2(24 char)
char(p), 1 <= p <= 255	varchar2(s char), 4 <= s <= 1020
clnt(p), 1 <= p <= 3	varchar2(s char), 4 <= s <= 12
cuky(p), 1 <= p <= 5	varchar2(s char), 4 <= s <= 20
curr(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
d16d(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
d16r	binary_double
d34d(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
d34r	binary_double
dats	date
dec(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
fltp	binary_double
int1	number(3)
int2	number(5)
int4	number(10)
int8	number(19)
lang(1)	varchar2(4 char)
lchr *	varchar2(1 char)
lraw *	blob null
numc(p), 1 <= p <= 255	varchar2(s char), 4 <= s <= 1020
quan(p,s), 1 <= p <= 38, 0 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
raw(p), 1 <= p <= 255	blob null
sstr(p), 1 <= p <= 1333	varchar2(s char), 4 <= s <= 4000
strg *	varchar2(1 char)
tims	timestamp(0)
unit(p), 1 <= p <= 5	varchar2(s char), 4 <= s <= 20
* SAP doesn't specify the maximum length for these data types.

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•d16s
•d34s
•prec
•varc

Additionally, application ingestion and replication jobs do not support the rstr data type.

If necessary, you can create custom data-type mappings when you define an application ingestion and replication task. For more information, see "Data Type Rules" in Configure an Oracle target.

SAP ODP Source and Snowflake Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with an SAP ODP source and a Snowflake target:

SAP ODP Source Data Type	Snowflake Target Data Type
accp(6)	varchar(24)
char(p), 1 <= p <= 255	varchar(p), 4 <= p <= 1020
clnt(p), 1 <= p <= 3	varchar(p), 4 <= p <= 12
cuky(p), 1 <= p <= 5	varchar(p), 4 <= p <= 20
curr(p,0), 1 <= p <= 38	integer
curr(p,s), 1 <= p <= 38, 1 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
d16d(p,0), 1 <= p <= 38	integer
d16d(p,s), 1 <= p <= 38, 1 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
d16r	float
d34d(p,0), 1 <= p <= 38	integer
d34d(p,s), 1 <= p <= 38, 1 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
d34r	float
dats	date
dec(p,0), 1 <= p <= 38	integer
dec(p,s), 1 <= p <= 38, 1 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
fltp	float
int1	number(3)
int2	number(5)
int4	number(10)
int8	number(19)
lang(1)	varchar(4)
lchr *	varchar(4)
lraw *	binary(1)
numc(p), 1 <= p <= 255	varchar(p), 4 <= p <= 1020
quan(p,0), 1 <= p <= 38	integer
quan(p,s), 1 <= p <= 38, 1 <= s <= 16	number(p,s), 1 <= p <= 38, 1 <= s <= 16
raw(p), 1 <= p <= 255	binary(p), 1 <= p <= 255
sstr(p), 1 <= p <= 1333	varchar(p), 4 <= p <= 5332
strg *	varchar(4)
tims	time(0)
unit(p), 1 <= p <= 5	varchar(p), 4 <= p <= 20
* SAP doesn't specify the maximum length for these data types.

Unsupported source data types

Application Ingestion and Replication does not support the following obsolete SAP data types:

•d16s
•d34s
•prec
•varc

Additionally, application ingestion and replication jobs do not support the rstr data type.

ServiceNow Source and Amazon Redshift Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a ServiceNow source and an Amazon Redshift target:

ServiceNow Source Data Type	Amazon Redshift Target Data Type
audio	character varying(p), 4 <= p <= 16000
boolean	boolean
choice	character varying(p), 4 <= p <= 16000
color	character varying(p), 4 <= p <= 16000
compressed	character varying(p), 4 <= p <= 16000
condition_string	character varying(p), 4 <= p <= 16000
conditions	character varying(p), 4 <= p <= 16000
currency(p,s), 1 <= p <= 18, 0 <= s <= 2	numeric(p,s), 1 <= p <= 18, 0 <= s <= 2
currency2	character varying(p), 4 <= p <= 16000
decimal(p,s), 1 <= p <= 20, 0 <= s <= 2	numeric(p,s), 1 <= p <= 20, 0 <= s <= 2
document_id	character varying(p), 4 <= p <= 16000
domain_id	character varying(p), 4 <= p <= 16000
domain_path	character varying(p), 4 <= p <= 16000
due_date	timestamp without time zone
field_name	character varying(p), 4 <= p <= 16000
file_attachment	character varying(p), 4 <= p <= 16000
float(p,s), 1 <= p <= 19, 0 <= s <= 7	numeric(p,s), 1 <= p <= 20, 0 <= s <= 7
glide_date	date
glide_date_time	timestamp without time zone
glide_duration	timestamp without time zone
glide_encrypted	character varying(p), 4 <= p <= 16000
glide_list	character varying(p), 4 <= p <= 16000
glide_time	timestamp without time zone
guid	character varying(p), 4 <= p <= 16000
html	character varying(p), 4 <= p <= 16000
icon	character varying(p), 4 <= p <= 16000
image	character varying(p), 4 <= p <= 16000
integer	integer
ip_addr	character varying(p), 4 <= p <= 16000
journal	character varying(p), 4 <= p <= 16000
journal_input	character varying(p), 4 <= p <= 16000
journal_list	character varying(p), 4 <= p <= 16000
longint	bigint
password	character varying(p), 4 <= p <= 16000
password2	character varying(p), 4 <= p <= 16000
percent_complete(p,s), 1 <= p <= 16, 0 <= s <= 2	numeric(p,s), 1 <= p <= 16, 0 <= s <= 2
phone_number_e164	character varying(p), 4 <= p <= 16000
price(p,s), 1 <= p <= 18, 0 <= s <= 2	numeric(p,s), 1 <= p <= 18, 0 <= s <= 2
reference	character varying(p), 4 <= p <= 16000
script	character varying(p), 4 <= p <= 16000
script_plain	character varying(p), 4 <= p <= 16000
simple_name_values	character varying(p), 4 <= p <= 16000
string	character varying(p), 4 <= p <= 16000
string_full_utf8	character varying(p), 4 <= p <= 16000
sys_class_name	character varying(p), 4 <= p <= 16000
sys_class_path	character varying(p), 4 <= p <= 16000
table_name	character varying(p), 4 <= p <= 16000
translated_field	character varying(p), 4 <= p <= 16000
translated_html	character varying(p), 4 <= p <= 16000
translated_text	character varying(p), 4 <= p <= 16000
url	character varying(p), 4 <= p <= 16000
user_image	character varying(p), 4 <= p <= 16000
user_roles	character varying(p), 4 <= p <= 16000
video	character varying(p), 4 <= p <= 16000
wiki_text	character varying(p), 4 <= p <= 16000
workflow	character varying(p), 4 <= p <= 16000

ServiceNow Source and Databricks Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a ServiceNow source and a Databricks target:

ServiceNow Source Data Type	Databricks Target Data Type
audio	string
boolean	boolean
choice	string
color	string
compressed	string
condition_string	string
conditions	string
currency(p,s), 1 <= p <= 18, 0 <= s <= 2	decimal(p,s), 1 <= p <= 18, 1 <= s <= 2
currency2	string
decimal(p,s), 1 <= p <= 20, 0 <= s <= 2	decimal(p,s), 1 <= p <= 20, 1 <= s <= 2
document_id	string
domain_id	string
domain_path	string
due_date	timestamp
field_name	string
file_attachment	string
float(p,s), 1 <= p <= 19, 0 <= s <= 7	decimal(p,s), 1 <= p <= 19, 1 <= s <= 7
glide_date	string
glide_date_time	timestamp
glide_duration	timestamp
glide_encrypted	string
glide_list	string
glide_time	timestamp
guid	string
html	string
icon	string
image	string
integer	integer
ip_addr	string
journal	string
journal_input	string
journal_list	string
longint	long
password	string
password2	string
percent_complete(p,s), 1 <= p <= 16, 0 <= s <= 2	decimal(p,s), 1 <= p <= 16, 1 <= s <= 2
phone_number_e164	string
price(p,s), 1 <= p <= 18, 0 <= s <= 2	decimal(p,s), 1 <= p <= 18, 1 <= s <= 2
reference	string
script	string
script_plain	string
simple_name_values	string
string	string
string_full_utf8	string
sys_class_name	string
sys_class_path	string
table_name	string
translated_field	string
translated_html	string
translated_text	string
url	string
user_image	string
user_roles	string
video	string
wiki_text	string
workflow	string

ServiceNow Source and Google BigQuery Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a ServiceNow source and a Google BigQuery target:

ServiceNow Source Data Type	Google BigQuery Target Data Type
audio	string
boolean	bool
choice	string
color	string
compressed	string
condition_string	string
conditions	string
currency(p,s), 1 <= p <= 18, 0 <= s <= 2	bignumeric
currency2	string
decimal(p,s), 1 <= p <= 20, 0 <= s <= 2	bignumeric
document_id	string
domain_id	string
domain_path	string
due_date	datetime
field_name	string
file_attachment	string
float(p,s), 1 <= p <= 19, 0 <= s <= 7	bignumeric
glide_date	date
glide_date_time	datetime
glide_duration	datetime
glide_encrypted	string
glide_list	string
glide_time	datetime
guid	string
html	string
icon	string
image	string
integer	int64
ip_addr	string
journal	string
journal_input	string
journal_list	string
longint	int64
password	string
password2	string
percent_complete(p,s), 1 <= p <= 16, 0 <= s <= 2	bignumeric
phone_number_e164	string
price(p,s), 1 <= p <= 18, 0 <= s <= 2	bignumeric
reference	string
script	string
script_plain	string
simple_name_values	string
string	string
string_full_utf8	string
sys_class_name	string
sys_class_path	string
table_name	string
translated_field	string
translated_html	string
translated_text	string
url	string
user_image	string
user_roles	string
video	string
wiki_text	string
workflow	string

ServiceNow Source and Microsoft Azure Synapse Analytics Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a ServiceNow source and a Microsoft Azure Synapse Analytics target:

ServiceNow Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
audio	varchar(p), 4 <= p <= max
boolean	bit
choice	varchar(p), 4 <= p <= max
color	varchar(p), 4 <= p <= max
compressed	varchar(p), 4 <= p <= max
condition_string	varchar(p), 4 <= p <= max
conditions	varchar(p), 4 <= p <= max
currency(p,s), 1 <= p <= 18, 0 <= s <= 2	decimal(p,s), 1 <= p <= 18, 1 <= s <= 2
currency2	varchar(p), 4 <= p <= max
decimal(p,s), 1 <= p <= 20, 0 <= s <= 2	decimal(p,s), 1 <= p <= 20, 1 <= s <= 2
document_id	varchar(p), 4 <= p <= max
domain_id	varchar(p), 4 <= p <= max
domain_path	varchar(p), 4 <= p <= max
due_date	datetime
field_name	varchar(p), 4 <= p <= max
file_attachment	varchar(p), 4 <= p <= max
float(p,s), 1 <= p <= 19, 0 <= s <= 7	decimal(p,s), 1 <= p <= 19, 1 <= s <= 7
glide_date	date
glide_date_time	datetime
glide_duration	datetime
glide_encrypted	varchar(p), 4 <= p <= max
glide_list	varchar(p), 4 <= p <= max
glide_time	datetime
guid	varchar(p), 4 <= p <= max
html	varchar(p), 4 <= p <= max
icon	varchar(p), 4 <= p <= max
image	varchar(p), 4 <= p <= max
integer	int
ip_addr	varchar(p), 4 <= p <= max
journal	varchar(p), 4 <= p <= max
journal_input	varchar(p), 4 <= p <= max
journal_list	varchar(p), 4 <= p <= max
longint	bigint
password	varchar(p), 4 <= p <= max
password2	varchar(p), 4 <= p <= max
percent_complete(p,s), 1 <= p <= 16, 0 <= s <= 2	decimal(p,s), 1 <= p <= 16, 1 <= s <= 2
phone_number_e164	varchar(p), 4 <= p <= max
price(p,s), 1 <= p <= 18, 0 <= s <= 2	decimal(p,s), 1 <= p <= 18, 1 <= s <= 2
reference	varchar(p), 4 <= p <= max
script	varchar(p), 4 <= p <= max
script_plain	varchar(p), 4 <= p <= max
simple_name_values	varchar(p), 4 <= p <= max
string	varchar(p), 4 <= p <= max
string_full_utf8	varchar(p), 4 <= p <= max
sys_class_name	varchar(p), 4 <= p <= max
sys_class_path	varchar(p), 4 <= p <= max
table_name	varchar(p), 4 <= p <= max
translated_field	varchar(p), 4 <= p <= max
translated_html	varchar(p), 4 <= p <= max
translated_text	varchar(p), 4 <= p <= max
url	varchar(p), 4 <= p <= max
user_image	varchar(p), 4 <= p <= max
user_roles	varchar(p), 4 <= p <= max
video	varchar(p), 4 <= p <= max
wiki_text	varchar(p), 4 <= p <= max
workflow	varchar(p), 4 <= p <= max

ServiceNow Source and Oracle Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a ServiceNow source and an Oracle target:

ServiceNow Source Data Type	Oracle Target Data Type
udio	char(s char), 4 <= s <= 2000
audio	clob
boolean	char(1 char)
choice	char(s char), 4 <= s <= 2000
choice	clob
color	char(s char), 4 <= s <= 2000
color	clob
compressed	char(s char), 4 <= s <= 2000
compressed	clob
condition_string	char(s char), 4 <= s <= 2000
condition_string	clob
conditions	char(s char), 4 <= s <= 2000
conditions	clob
currency(p,s), 1 <= p <= 18, 0 <= s <= 2	number(p,s), 1 <= p <= 18, 1 <= s <= 2
currency2	char(s char), 4 <= s <= 2000
currency2	clob
decimal(p,s), 1 <= p <= 20, 0 <= s <= 2	number(p,s), 1 <= p <= 20, 1 <= s <= 2
document_id	char(s char), 4 <= s <= 2000
document_id	clob
domain_id	char(s char), 4 <= s <= 2000
domain_id	clob
domain_path	char(s char), 4 <= s <= 2000
domain_path	clob
due_date	date
field_name	char(s char), 4 <= s <= 2000
field_name	clob
file_attachment	char(s char), 4 <= s <= 2000
file_attachment	clob
float(p,s), 1 <= p <= 19, 0 <= s <= 7	number(p,s), 1 <= p <= 19, 1 <= s <= 7
glide_date	date
glide_date_time	date
glide_duration	date
glide_encrypted	char(s char), 4 <= s <= 2000
glide_encrypted	clob
glide_list	char(s char), 4 <= s <= 2000
glide_list	clob
glide_time	date
guid	char(s char), 4 <= s <= 2000
guid	clob
html	char(s char), 4 <= s <= 2000
html	clob
icon	char(s char), 4 <= s <= 2000
icon	clob
image	char(s char), 4 <= s <= 2000
image	clob
integer	number(10)
ip_addr	char(s char), 4 <= s <= 2000
ip_addr	clob
journal	char(s char), 4 <= s <= 2000
journal	clob
journal_input	char(s char), 4 <= s <= 2000
journal_input	clob
journal_list	char(s char), 4 <= s <= 2000
journal_list	clob
longint	number(19)
password	char(s char), 4 <= s <= 2000
password	clob
password2	char(s char), 4 <= s <= 2000
password2	clob
percent_complete(p,s), 1 <= p <= 16, 0 <= s <= 2	number(p,s), 1 <= p <= 16, 1 <= s <= 2
phone_number_e164	char(s char), 4 <= s <= 2000
phone_number_e164	clob
price(p,s), 1 <= p <= 18, 0 <= s <= 2	number(p,s), 1 <= p <= 18, 1 <= s <= 2
reference	char(s char), 4 <= s <= 2000
reference	clob
script	char(s char), 4 <= s <= 2000
script	clob
script_plain	char(s char), 4 <= s <= 2000
script_plain	clob
simple_name_values	char(s char), 4 <= s <= 2000
simple_name_values	clob
string	char(s char), 4 <= s <= 2000
string	clob
string_full_utf8	char(s char), 4 <= s <= 2000
string_full_utf8	clob
sys_class_name	char(s char), 4 <= s <= 2000
sys_class_name	clob
sys_class_path	char(s char), 4 <= s <= 2000
sys_class_path	clob
table_name	char(s char), 4 <= s <= 2000
table_name	clob
translated_field	char(s char), 4 <= s <= 2000
translated_field	clob
translated_html	char(s char), 4 <= s <= 2000
translated_html	clob
translated_text	char(s char), 4 <= s <= 2000
translated_text	clob
url	char(s char), 4 <= s <= 2000
url	clob
user_image	char(s char), 4 <= s <= 2000
user_image	clob
user_roles	char(s char), 4 <= s <= 2000
user_roles	clob
video	char(s char), 4 <= s <= 2000
video	clob
wiki_text	char(s char), 4 <= s <= 2000
wiki_text	clob
workflow	char(s char), 4 <= s <= 2000
workflow	clob

ServiceNow Source and Snowflake Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a ServiceNow source and a Snowflake target:

ServiceNow Source Data Type	Snowflake Target Data Type
audio	char(p), 4 <= p <= 16000
boolean	boolean
choice	char(p), 4 <= p <= 16000
color	char(p), 4 <= p <= 16000
compressed	char(p), 4 <= p <= 16000
condition_string	char(p), 4 <= p <= 16000
conditions	char(p), 4 <= p <= 16000
currency(p,0), 1 <= p <= 18	integer
currency(p,s), 1 <= p <= 18, 1 <= s <= 2	number(p,s), 1 <= p <= 18, 1 <= s <= 2
currency2	char(p), 4 <= p <= 16000
decimal(p,0), 1 <= p <= 20	integer
decimal(p,s), 1 <= p <= 20, 1 <= s <= 2	number(p,s), 1 <= p <= 20, 1 <= s <= 2
document_id	char(p), 4 <= p <= 16000
domain_id	char(p), 4 <= p <= 16000
domain_path	char(p), 4 <= p <= 16000
due_date	datetime(0)
field_name	char(p), 4 <= p <= 16000
file_attachment	char(p), 4 <= p <= 16000
float(p,0), 1 <= p <= 19	integer
float(p,s), 1 <= p <= 19, 1 <= s <= 7	number(p,s), 1 <= p <= 19, 1 <= s <= 7
glide_date	date
glide_date_time	datetime(0)
glide_duration	datetime(0)
glide_encrypted	char(p), 4 <= p <= 16000
glide_list	char(p), 4 <= p <= 16000
glide_time	datetime(0)
guid	char(p), 4 <= p <= 16000
html	char(p), 4 <= p <= 16000
icon	char(p), 4 <= p <= 16000
image	char(p), 4 <= p <= 16000
integer	number(10)
ip_addr	char(p), 4 <= p <= 16000
journal	char(p), 4 <= p <= 16000
journal_input	char(p), 4 <= p <= 16000
journal_list	char(p), 4 <= p <= 16000
longint	number(19)
password	char(p), 4 <= p <= 16000
password2	char(p), 4 <= p <= 16000
percent_complete(p,0), 1 <= p <= 16	integer
percent_complete(p,s), 1 <= p <= 16, 1 <= s <= 2	number(p,s), 1 <= p <= 16, 1 <= s <= 2
phone_number_e164	char(p), 4 <= p <= 16000
price(p,0), 1 <= p <= 18	integer
price(p,s), 1 <= p <= 18, 1 <= s <= 2	number(p,s), 1 <= p <= 18, 1 <= s <= 2
reference	char(p), 4 <= p <= 16000
script	char(p), 4 <= p <= 16000
script_plain	char(p), 4 <= p <= 16000
simple_name_values	char(p), 4 <= p <= 16000
string	char(p), 4 <= p <= 16000
string_full_utf8	char(p), 4 <= p <= 16000
sys_class_name	char(p), 4 <= p <= 16000
sys_class_path	char(p), 4 <= p <= 16000
table_name	char(p), 4 <= p <= 16000
translated_field	char(p), 4 <= p <= 16000
translated_html	char(p), 4 <= p <= 16000
translated_text	char(p), 4 <= p <= 16000
url	char(p), 4 <= p <= 16000
user_image	char(p), 4 <= p <= 16000
user_roles	char(p), 4 <= p <= 16000
video	char(p), 4 <= p <= 16000
wiki_text	char(p), 4 <= p <= 16000
workflow	char(p), 4 <= p <= 16000

Workday Source and Amazon Redshift Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Workday source and an Amazon Redshift target:

Workday Source Data Type	Amazon Redshift Target Data Type
json	super
string	character varying(p), 4 <= p <= 4000
xml	character varying(65535)
xsd	numeric(p,s), 1 <= p <= 38, 0 <= s <= 37
xsd:boolean	boolean
xsd:date	date
xsd:datetime	timestamp with time zone
xsd:string	character varying(p), 4 <= p <= 4000

Workday Source and Databricks Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Workday source and a Databricks target:

Workday Source Data Type	Databricks Target Data Type
json	string
string	string
xml	string
xsd	decimal(p,s), 1 <= p <= 38, 0 <= s <= 37
xsd:boolean	boolean
xsd:date	string
xsd:datetime	timestamp
xsd:string	string

Workday Source and Google BigQuery Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Workday source and a Google BigQuery target:

Workday Source Data Type	Google BigQuery Target Data Type
json	string
string	string
xml	string
xsd	bignumeric
xsd:boolean	bool
xsd:date	date
xsd:datetime	timestamp
xsd:string	string

Workday Source and Microsoft Azure Synapse Analytics Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Workday source and a Microsoft Azure Synapse Analytics target:

Workday Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
json	nvarchar(max)
string	nchar(p), 1 <= p <= 1000
xml	nvarchar(max)
xsd	decimal(p,s), 1 <= p <= 38, 0 <= s <= 37
xsd:boolean	bit
xsd:date	date
xsd:datetime	datetimeoffset(3)
xsd:string	nchar(p), 1 <= p <= 1000

Workday Source and Oracle Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Workday source and an Oracle target:

Workday Source Data Type	Oracle Target Data Type
json	clob
string	char(s char), 4 <= s <= 2000
xml	clob
xsd	number(p,s), 1 <= p <= 38, 0 <= s <= 37
xsd:boolean	char(1 char)
xsd:date	date
xsd:datetime	timestamp(p) with time zone, 3 <= p <= null
xsd:string	char(s char), 4 <= s <= 2000

Workday Source and Snowflake Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Workday source and a Snowflake target:

Workday Source Data Type	Snowflake Target Data Type
json	variant
string	char(p), 4 <= p <= 4000
xml	variant
xsd	integer
xsd	number(38,s), 1 <= s <= 37
xsd	number(p,s), 1 <= p <= 37, 1 <= s <= 37
xsd:boolean	boolean
xsd:date	date
xsd:datetime	timestamp_tz(3)
xsd:string	char(p), 4 <= p <= 4000

Zendesk Source and Amazon Redshift Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Zendesk source and an Amazon Redshift target:

Zendesk Source Data Type	Amazon Redshift Target Data Type
array	character varying(65535)
boolean	boolean
datetime	timestamp without time zone
integer	bigint
json	character varying(65535)
object	character varying(65535)
string	character varying(40960)
string_long	character varying(65535)
string_short	character varying(4096)

Zendesk Source and Databricks Target

The following table identifies the recommended data type mappings for Application Ingestion and Replicationconfigurations with a Zendesk source and a Databricks target:

Zendesk Source Data Type	Databricks Target Data Type
array	string
boolean	boolean
datetime	timestamp
integer	long
json	string
object	string
string	string
string_long	string
string_short	string

Zendesk Source and Google BigQuery Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Zendesk source and a Google BigQuery target:

Zendesk Source Data Type	Google BigQuery Target Data Type
array	string
boolean	bool
datetime	datetime
integer	int64
json	string
object	string
string	string
string_long	string
string_short	string

Zendesk Source and Microsoft Azure Synapse Analytics Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Zendesk and a Microsoft Azure Synapse Analytics target:

Zendesk Source Data Type	Microsoft Azure Synapse Analytics Target Data Type
array	varchar(max)
boolean	bit
datetime	datetime
integer	bigint
json	nvarchar(max)
object	varchar(max)
string	varchar(max)
string_long	varchar(max)
string_short	varchar(4096)

Zendesk Source and Oracle Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Zendesk source and an Oracle target:

Zendesk Source Data Type	Oracle Target Data Type
array	clob
boolean	char(1 char)
datetime	timestamp(3)
integer	number(19)
json	clob
object	clob
string	clob
string_long	clob
string_short	char(2000 char)

Zendesk Source and Snowflake Target

The following table identifies the recommended data type mappings for Application Ingestion and Replication configurations with a Zendesk source and a Snowflake target:

Zendesk Source Data Type	Snowflake Target Data Type
array	char(16777216)
boolean	boolean
datetime	datetime(3)
integer	integer
json	variant
object	char(16777216)
string	char(40960)
string_long	char(4194304)
string_short	char(4096)