When you use a Snowflake ODBC connection and select the ODBC subtype as Snowflake, you can configure SQL ELT optimization in a mapping to push transformation logic to the Snowflake Cloud Data Warehouse source or target database. The ODBC connection must use the Snowflake ODBC driver.
When you run a task configured for SQL ELT optimization, the task converts the transformation logic to an SQL query. The task sends the query to the database, and the database executes the query. Use SQL ELT optimization to improve the performance of the task.
You can configure full and source SQL ELT optimization in a Snowflake mapping.
For more information about SQL ELT optimization using the Snowflake ODBC connection, see the SQL ELT optimization chapter in the help for ODBC Connector or Snowflake Data Cloud Connector.
Example
You are a sales manager in a rapidly growing manufacturing organization. Your organization stores the product transaction details such as transactionID, customerID, productID, quantity, product_revenue, and OrderDate in Snowflake database. You need to calculate the total revenue generated from the sales of a particular product. Use Snowflake Connector to create a mapping to read all the product revenue details of a particular product from the Snowflake source, apply aggregate function to calculate the total revenue, and write the records to Snowflake target for data analysis.
The organization plans to implement a business intelligence service to build visualization and perform real-time analysis. Therefore, you need to port the vast amount of data stored in Snowflake database to the business intelligence service. You can use Snowflake Connector to read data from Snowflake. To read this large amount of data, you can use full or source SQL ELT optimization for the ODBC connection type. Using the ODBC connection type with SQL ELT optimization enhances the performance.