Amazon Redshift supports ALTER TABLE and writes for Iceberg tables
Amazon Redshift now allows writing directly to Apache Iceberg tables via the AWS Glue Data Catalog and supports ALTER TABLE DDL statements for schema modifications. This simplifies data pipelines by enabling transformations in the data lake that are queryable by any engine, eliminating the need to delete and recreate tables. These enhancements ensure cross-engine interoperability with engines like EMR and Athena and are available in all AWS Regions.
- →Direct writes to Iceberg tables via AWS Glue Data Catalog mount
- →ALTER TABLE DDL for schema, partitioning, and properties modification
- →Supports AWS Lake Formation permissions for write operations
- →Preserves cross-engine interoperability with Iceberg
Features (3) ›
- Direct writes to Iceberg tables via AWS Glue Data Catalog mount
Amazon Redshift now supports writing directly to Apache Iceberg tables through the auto-mounted AWS Glue Data Catalog. This enables Redshift transformations to be landed in the data lake for querying by any engine, simplifying data pipelines and integration with AWS Lake Formation.
- ALTER TABLE DDL for schema, partitioning, and properties modification
Users can now modify the schema, partitioning, and properties of Apache Iceberg tables using ALTER TABLE DDL statements. Supported operations include column modifications, renaming, table properties overwrites, and partition field changes, addressing previous limitations that required table deletion and recreation.
- Supports AWS Lake Formation permissions for write operations
Write operations to Iceberg tables from Amazon Redshift now support AWS Lake Formation permissions. This allows for centralized permission management and governance of data lake operations.
Enhancements (1) ›
- Preserves cross-engine interoperability with Iceberg
Tables modified by Amazon Redshift remain compatible with other Iceberg-compatible engines, such as Amazon EMR and Amazon Athena. This ensures that data modified in Redshift can still be queried and processed by other tools in the data ecosystem.
https://aws.amazon.com/about-aws/whats-new/2026/05/amazon-redshift-alter-table-iceberg/
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