Aurora PostgreSQL now supports querying of Apache Iceberg and Parquet data
Aurora PostgreSQL now supports querying of Apache Iceberg and Parquet data Aurora PostgreSQL now supports querying of Apache Iceberg and Parquet data Posted on: Sep 30, 2026 Starting today, you can directly query operational data together with data stored in data lakes in Apache Iceberg and Parquet formats using your existing PostgreSQL applications and tools, without extract, transform, and load (ETL) pipelines or data duplication. Applications increasingly need access to data from data lakes, often stored in Apache Iceberg and Parquet formats, to make more informed decisions and automate business processes.
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- Aurora PostgreSQL now supports querying of Apache Iceberg and Parquet data Posted on: Sep 30, 2026 Starting today, you can directly query operational data together with data stored in data lakes in Apache Iceberg and Parquet formats using your existing PostgreSQL applications and tools, without extract, transform, and load (ETL) pipelines or data duplication.
- Applications increasingly need access to data from data lakes, often stored in Apache Iceberg and Parquet formats, to make more informed decisions and automate business processes.
- Accessing it has typically required pipelines that copy data from your data lake into Aurora, driving up costs and engineering work as schemas evolve.
- With this launch, you can create PostgreSQL foreign tables that reference your Iceberg or Parquet data in Amazon S3, Amazon S3 Tables, or AWS Glue Data Catalog.
- When customers query these foreign tables, Aurora uses DuckDB’s high-performance query engine, embedded in PostgreSQL, to execute the query against the underlying Iceberg and Parquet data.
- Your existing applications and BI tools continue to use the same PostgreSQL interface.