Amazon Web Services has added native support for querying Apache Iceberg and Apache Parquet data lakes directly from its Aurora PostgreSQL database management system. By embedding the DuckDB analytical engine directly into Aurora, the platform allows applications to run analytical queries combining live operational transactions with historical records stored in Amazon S3, eliminating the need to move data or maintain traditional extract, transform, and load (ETL) pipelines.
DuckDB Integration Eliminates Reverse ETL Pipelines
The update follows AWS's acquisition of DuckDB creator DuckLabs B.V. and marks a significant push to embed the analytical database across AWS infrastructure. Previously, combining active operational tables in Aurora with archived records in S3 required complex reverse ETL pipelines that introduced data duplication, extra infrastructure costs, and synchronization overhead.
With the embedded DuckDB engine, analytical processing happens directly inside Aurora without extra network hops. A single SQL query can access live, uncommitted operational writes alongside data lake records. Aurora handles query performance by filtering records and selecting relevant columns during execution while caching frequently accessed data.
Support for External Catalogs and Schema Inference
The feature supports catalogs conforming to the Iceberg REST Catalog specification via federation with AWS Glue. Developers register an external catalog in Glue to set up foreign tables, letting PostgreSQL applications join local Aurora data with Iceberg datasets across external catalogs. Aurora can also infer historical schemas directly from file metadata, removing the requirement to manually map table structures.
For latency-critical applications targeting single-digit millisecond performance, teams can copy data lake records directly into native Aurora tables using standard SQL. Read queries can be offloaded to read replicas, whereas operations that materialize data execute on the cluster writer node.
Setup and Regional Availability
The analytical capability is available in all commercial AWS regions without an upfront feature fee. Users pay for the underlying compute resources consumed by queries and the standard S3 request charges for reading file objects.
Enabling the feature requires activating the aurora_analytics extension and configuring an AWS Identity and Access Management role to permit S3 and AWS Glue access. The integration supports Aurora PostgreSQL engine versions 17.11 and 18.6 or newer.
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Source: AWS embeds DuckDB in its PostgreSQL DBMS to speed queries of live and historical data
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