What's New and Changed > Part V: Version 10.2.1 > 10.2.1 What's New > PowerExchange Adapters for Informatica

PowerExchange Adapters for Informatica

This section describes new Informatica adapter features in version 10.2.1.

PowerExchange for Amazon Redshift

Effective in version 10.2.1, PowerExchange for Amazon Redshift includes the following features:

•You can configure a cached lookup operation to cache the lookup table on the Spark engine and an uncached lookup operation in the native environment.
•For a server-side encryption, you can configure the customer master key ID generated by AWS Key Management Service in the connection in the native environment and Spark engine.

For more information, see the Informatica PowerExchange for Amazon Redshift 10.2.1 User Guide.

PowerExchange for Amazon S3

Effective in version 10.2.1, PowerExchange for Amazon S3 includes the following features:

•For a client-side encryption, you can configure the customer master key ID generated by AWS Key Management Service in the connection in the native environment. For a server-side encryption, you can configure the customer master key ID generated by AWS Key Management Service in the connection in the native environment and Spark engine.
•For a server-side encryption, you can configure the Amazon S3-managed encryption key or AWS KMS-managed customer master key to encrypt the data while uploading the files to the buckets.
•You can create an Amazon S3 file data object from the following data source formats in Amazon S3:

- Intelligent Structure Model

The intelligent structure model feature for PowerExchange for Amazon S3 is available for technical preview. Technical preview functionality is supported but is not production-ready. Informatica recommends that you use in non-production environments only.

- JSON
- ORC

•You can compress an ORC data in the Zlib compression format when you write data to Amazon S3 in the native environment and Spark engine.
•You can create an Amazon S3 target using the Create Target option in the target session properties.
•You can use complex data types on the Spark engine to read and write hierarchical data in the Avro and Parquet file formats.
•You can use Amazon S3 sources as dynamic sources in a mapping. Dynamic mapping support for PowerExchange for Amazon S3 sources is available for technical preview. Technical preview functionality is supported but is unwarranted and is not production-ready. Informatica recommends that you use these features in non-production environments only.

For more information, see the Informatica PowerExchange for Amazon S3 10.2.1 User Guide.

PowerExchange for Cassandra

Effective in version 10.2.1, the Informatica Cassandra ODBC driver supports asynchronous write.

To enable asynchronous write on a Linux operating system, you must add the EnableAsynchronousWrites key name in the odbc.ini file and set the value to 1.

To enable asynchronous write on a Windows operating system, you must add the EnableAsynchronousWrites property in the Windows registry for the Cassandra ODBC data source name and set the value as 1.

For more information, see the Informatica PowerExchange for Cassandra 10.2.1 User Guide.

PowerExchange for HBase

Effective in version 10.2.1, you can use an HBase data object read operation to look up data in an HBase resource. Run the mapping in the native environment or on the Spark engine to look up data in an HBase resource. You can enable lookup caching and also parameterize the lookup condition.

The lookup feature for PowerExchange for HBase is available for technical preview. Technical preview functionality is supported but is not production-ready. Informatica recommends that you use in non-production environments only.

For more information, see the Informatica PowerExchange for HBase 10.2.1 User Guide.

PowerExchange for HDFS

Effective in version 10.2.1, you can use the following new PowerExchange for HDFS features:

Intelligent structure model support for complex file data objects
Dynamic mapping support for complex file sources

PowerExchange for Hive

Effective in version 10.2.1, PowerExchange for Hive supports mappings that run PreSQL and PostSQL queries against Hive sources and targets on the Spark engine.

For more information, see the Informatica PowerExchange for Hive 10.2.1 User Guide.

PowerExchange for Microsoft Azure Blob Storage

Effective in version 10.2.1, PowerExchange for Microsoft Azure Blob Storage includes the following functionality:

•You can run mappings on the Spark engine.
•You can read and write .csv, Avro, and Parquet files when you run a mapping on the Spark engine and in the native environment.
•You can read and write JSON and intelligent structure files when you run a mapping on the Spark engine.
•You can read a directory when you run a mapping on the Spark engine.
•You can generate or skip header rows when you run a mapping in the native environment. On the Spark engine, the header row is created by default.
•You can append an existing blob. The append operation is applicable to only to the append blob and in the native environment.
•You can override the blob or container name. In the Blob Container Override field, specify the container name or sub-folders in the root container with the absolute path.
•You can read and write .csv files compressed in the gzip format.

All new functionality for PowerExchange for Microsoft Azure Blob Storage is available for technical preview. Technical preview functionality is supported but is not production-ready. Informatica recommends that you use in non-production environments only.

For more information, see the Informatica PowerExchange for Microsoft Azure Blob Storage 10.2.1 User Guide.

PowerExchange for Microsoft Azure SQL Data Warehouse

Effective in version 10.2.1, PowerExchange for Microsoft Azure SQL Data Warehouse includes the following features:

•You can run mappings on the Spark engine.
•You can configure key range partitioning when you read data from Microsoft Azure SQL Data Warehouse objects.
•You can override the SQL query and define constraints when you read data from a Microsoft Azure SQL Data Warehouse object.
•You can configure pre-SQL and post-SQL queries for source and target objects in a mapping.
•You can configure the native expression filter for the source data object operation.
•You can perform update, upsert, and delete operations against Microsoft Azure SQL Data Warehouse tables.
•You can configure a cached lookup operation to cache the lookup table on the Spark engine and an uncached lookup operation in the native environment.

For more information, see the Informatica PowerExchange for Microsoft Azure SQL Data Warehouse 10.2.1 User Guide.

PowerExchange for Salesforce

Effective in version 10.2.1, you can use version 41 of Salesforce API to create a Salesforce connection and access Salesforce objects. You can use big objects with source and target transformations.

For more information, see the Informatica PowerExchange for Salesforce 10.2.1 User Guide.

PowerExchange for SAP NetWeaver

Effective in version 10.2.1, you can run mappings on the Spark engine to read data from SAP tables.

For more information, see the Informatica PowerExchange for SAP NetWeaver 10.2.1 User Guide.

PowerExchange for Snowflake

Effective in version 10.2.1, PowerExchange for Snowflake includes the following features:

•You can configure a lookup operation on a Snowflake table. You can also enable lookup caching for a lookup operation to increase the lookup performance. The Data Integration Service caches the lookup source and runs the query on the rows in the cache.
•You can parameterize the Snowflake connection, and data object read and write operation properties.
•You can configure key range partitioning for Snowflake data objects in a read or write operation. The Data Integration Service distributes the data based on the port or set of ports that you define as the partition key.
•You can specify a table name in the advanced target properties to override the table name in the Snowflake connection properties.

For more information, see the Informatica PowerExchange for Snowflake 10.2.1 User Guide.