Amazon Redshift adds support for creating and refreshing Apache Iceberg materialized views
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Amazon Redshift now supports creating and refreshing Apache Iceberg materialized views that pre-compute expensive joins and aggregations and store results in Apache Iceberg tables.
- Materialized views created with CREATE MATERIALIZED VIEW ... USING ICEBERG syntax
- Results stored as Iceberg tables in S3 or S3 table buckets, registered in AWS Glue Data Catalog
- Instantly queryable by Iceberg-compatible engines including Athena, Spark on EMR, Glue, Trino, and Snowflake
- Manual incremental refresh recomputes only changed data to keep views current
- Eliminates redundant expensive joins and aggregations across multiple users and teams
- Enables end-to-end pipelines using single engine without multi-engine orchestration overhead
- Available in regions supporting Redshift Serverless and provisioned Graviton instances
Iceberg materialized views reduce pipeline complexity and enable open data sharing across multiple analytics engines without copies or conversion.
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