● Covered by 1 source · 1 reportMedium impact1 neutral
Amazon Aurora PostgreSQL now supports direct querying of Apache Iceberg and Parquet data
Key points
- Aurora PostgreSQL directly queries Iceberg and Parquet data.
- Eliminates ETL for data lake integration.
- Uses existing PostgreSQL applications and tools.
- DuckDB is embedded within Aurora PostgreSQL for query processing.
Direct Data Lake Querying
Amazon Aurora PostgreSQL now supports direct querying of Apache Iceberg and Apache Parquet data stored in data lakes. This new capability allows users to combine operational data with data lake information using existing PostgreSQL applications and tools.
Reduced Operational Complexity
The direct querying feature removes the need for extract, transform, and load (ETL) processes to move structured data from data lakes into operational databases. This reduces operational complexity and simplifies application development, particularly for tasks like powering real-time dashboards or enriching transactions with historical context.
Integration with DuckDB
This capability integrates technology from DuckDB, which is now embedded directly within Aurora PostgreSQL. This allows for querying live operational data alongside data lake data in a single query, with query processing remaining within Aurora without additional network hops or data duplication.
Broad Data Access
Users can query Apache Iceberg tables managed through the AWS Glue Data Catalog, as well as Parquet and Iceberg data in Amazon S3 and S3 Tables. The integration also supports Iceberg REST Catalog (IRC)-compatible catalogs, providing access to data across various analytics systems without data movement or duplication.
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Reporting from
Amazon Aurora PostgreSQL now allows direct querying of Apache Iceberg and Parquet data in data lakes, eliminating the need for ETL processes. This integration simplifies combining operational and historical data, reducing operational complexity and supporting AI applications.