Amazon Redshift now supports creating and refreshing Apache Iceberg materialized views, allowing for efficient data processing and query performance across multiple engines.
Why it matters. Data teams can now leverage a single engine for end-to-end pipelines and share open Iceberg tables without the overhead of orchestrating multiple engines.
You can create Iceberg Materialized Views in any region where Redshift Serverless and provisioned Graviton instances are supported.
This adds pipeline orchestration overhead and can introduce semantic differences between engines. Iceberg materialized views deliver value in two ways. First, instead of hundreds of users and teams re-running the same expensive joins and aggregations, and re-scanning source tabl…
Amazon Redshift now supports the creation and refresh of Apache Iceberg materialized views. Materialized views pre-compute expensive joins and aggregations once and store the results in an Apache Iceberg table in Amazon S3 or Amazon S3 table buckets, registered in the AWS Glue D…
