Use pushdown optimization to improve mapping performance by using the database resources. When you run a mapping configured for pushdown optimization, the mapping converts the transformation logic to an SQL query. The mapping sends the query to the database, and the database executes the query.

Amazon Redshift supports source-side and full pushdown optimization for mappings. You can perform insert, update, or delete operation in a pushdown optimization.

Example

: 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 Redshift Services and stores its data in Amazon Redshift database, a petabyte-scale 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 one database of Amazon Redshift to another Amazon Redshift database. Then, use MPP to run high-performance analytics.

You can use an ODBC connection to read this large amount of data from and write data to Amazon Redshift. Use full pushdown for the ODBC connection type to enhance the performance.

To read data from and write data to a Amazon Redshift object using the OBDC connection, perform the following steps:

Download and install the Amazon Redshift ODBC driver.
Configure a system DSN.
Create an ODBC connection to access the Amazon Redshift read and write data objects.
Import the Amazon Redshift read and write data objects.
Create and run a mapping.