SUPER data type and materialized views - Amazon Redshift

Amazon Redshift will no longer support the creation of new Python UDFs starting November 1, 2025. If you would like to use Python UDFs, create the UDFs prior to that date. Existing Python UDFs will continue to function as normal. For more information, see the blog post .

SUPER data type and materialized views

With Amazon Redshift, you can use the SUPER data type to enhance the performance and flexibility of materialized views. The SUPER data type lets you store a superset of columns from the base tables in a materialized view, letting you query the materialized view directly without joining the base tables. The following sections show you how to create and use materialized views with the SUPER data type in Amazon Redshift.

Amazon Redshift extends the capability of materialized views to work with the SUPER data type and PartiQL in materialized views. SQL and PartiQL queries can be precomputed using incremental materialized views. For more information about materialized views, see Materialized views in Amazon Redshift.

Once you have stored your schemaless and semistructured data into SUPER, you can use PartiQL materialized views to introspect the data and shred them into materialized views.