How to use streamlined permissions for Amazon S3 Tables and Iceberg materialized views
Big Data Blog
This article explains how to use streamlined IAM-based permissions for Amazon S3 Tables and Iceberg materialized views across AWS analytics services.
- S3 Tables provide fully managed Apache Iceberg experience integrated with AWS Glue Data Catalog
- Single IAM policy defines permissions across storage, catalog, and compute layers
- Iceberg materialized views store pre-computed query results on S3 for performance optimization
- Materialized views support scheduled or manual refresh intervals to keep data current
- Compatible with Amazon Athena, EMR, Redshift, and AWS Glue query engines
- Walkthrough covers setup, creating materialized views, and querying across multiple services
- AWS Lake Formation available for fine-grained access controls when needed
S3 Tables with IAM authorization simplify data lake governance by consolidating permissions into single policies, reducing operational complexity while maintaining enterprise security.
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