You can use pushdown optimization to push transformation logic to source databases or target databases. Use pushdown optimization when using database resources can improve task performance.
When you run a task configured for pushdown 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.
Amazon Redshift Connector supports
pushdown optimization for the ODBC connection type that uses Amazon ODBC Redshift drivers for mapping.
Amazon Redshift does not support upsert operation in a full pushdown optimization.
You work for a rapidly growing data science organization. Your organization develops software products to analyze financials, building financial graphs connecting people profiles, companies, jobs, advertisers, and publishers. The organization uses infrastructure based on Amazon Web Services and stores its data in Amazon Redshift, a petabytescale data warehouse. 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 Amazon Redshift to the business intelligence service. You can use Amazon Redshift Connector to read data from Amazon Redshift. To read this large amount of data, you can use source pushdown for the ODBC connection type. Using the ODBC connection type with pushdown optimization enhances the performance.