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Crunchy Data Unveils Ultra-High-Performance Analytics Database for the Postgres Ecosystem


Crunchy Data, the leading provider of trusted open source Postgres technology and products, is debuting Crunchy Data Warehouse, a high-performance, Postgres-native analytics database available as a managed service on Crunchy Bridge—the managed PostgreSQL platform from Crunchy Data. With full Iceberg support built on unmodified Postgres, Crunchy Data Warehouse offers fast analytical queries and transactions to support the familiar features and ecosystem of Postgres.

Crunchy Data Warehouse combines regular Postgres tables and fully transactional Iceberg tables, as well as integrates with the DuckDB query engine and other OLAP technologies, to support high-performance analytical workloads and operations database workloads. This amalgamation of tech creates extremely fast analytics delivered within a Postgres-native experience that stays current with the latest version of Postgres, ensuring that compatibility with the ecosystem is not lost, according to Crunchy Data.

"Crunchy Data Warehouse is a modern developer-friendly data warehouse built on PostgreSQL and DuckDB, using a lightweight, server-based architecture that's optimized for efficient use of hardware and predictable cost," said Craig Kerstiens, chief product officer, Crunchy Data. "Crunchy Data Warehouse extends unmodified PostgreSQL, ensuring that Crunchy Data Warehouse users can benefit from the broad ecosystem of PostgreSQL features, tools, and extensions you already know and love."

Crunchy Data Warehouse allows its users to create, manage, query, and update Iceberg tables stored in S3 as easily as PostgreSQL tables, all while delivering over 10x the average performance of PostgreSQL on TPC-H queries, according to the vendor. This also paves the way for improved performance for many common query patterns.

The introduction of Iceberg tables empowers interoperability with a wide range of analytics tools, allowing Crunchy Data Warehouse to interface with tools like Apache Spark for querying tables directly in S3 storage. Data files and directories can be seamlessly queried into a customer’s data lake, paired with the ability to load data directly from S3 into Iceberg or regular PostgreSQL tables. Query results can then be written back to S3 for the purpose of creating advanced data pipelines, offering flexible data import and export.

To learn more about Crunchy Data Warehouse, please visit https://www.crunchydata.com/.


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