Aurora PostgreSQL now lets PostgreSQL applications and BI tools query data stored in Apache Iceberg and Parquet formats in data lakes without ETL or data duplication. Developers can create PostgreSQL foreign tables that reference Iceberg or Parquet files in Amazon S3, Amazon S3 Tables, or through AWS Glue Data Catalog; queries against those foreign tables are executed by an embedded DuckDB high-performance engine inside PostgreSQL. This avoids copying data into the database as schemas evolve, reducing pipeline engineering and storage costs, while preserving the existing PostgreSQL interface and client tooling.
The feature also supports federated access to Iceberg tables exposed via IRC-compatible catalogs through AWS Glue, and offers a materialization path for latency-sensitive workloads by converting Iceberg/Parquet data into native Aurora PostgreSQL tables with standard SQL (no separate ETL). It is generally available at no extra charge on Aurora PostgreSQL versions 17.11, 18.6 and later across commercial and GovCloud (US) Regions. Users can enable it via the Amazon RDS console or any PostgreSQL client and consult documentation and blog guidance for setup details.
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