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This integration embeds the DuckDB analytical engine directly into Aurora PostgreSQL, enabling seamless querying of both live transactions and historical data stored in Apache Iceberg or Parquet formats. By eliminating the need for separate extract/transform/load pipelines, this move reduces infrastructure costs and simplifies data access for applications increasingly reliant on AI agents requiring unified real-time and archived datasets.

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AWS embeds DuckDB in its PostgreSQL DBMS to speed queries of live and historical data

SiliconANGLESeptember 30, 20264 min read

Amazon Web Services Inc. is adding the ability to query the popular Apache Iceberg data lake directly from its Aurora PostgreSQL database management system, allowing applications to combine live transactions with historical records without copying data or creating extract/transform/load pipelines. The capability embeds the DuckDB analytical engine inside Aurora PostgreSQL to support data stored in […] The post AWS embeds DuckDB in its PostgreSQL DBMS to speed queries of live and historical data appeared first on SiliconANGLE.

Amazon Web Services Inc. is adding the ability to query the popular Apache Iceberg data lake directly from its Aurora PostgreSQL database management system, allowing applications to combine live transactions with historical records without copying data or creating extract/transform/load pipelines. The capability embeds the DuckDB analytical engine inside Aurora PostgreSQL to support data stored in Iceberg and Apache Parquet formats. Customers can use existing PostgreSQL applications, tools…

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