Starburst Introduces Python Support for Complex Data Transformation and Data Application Workloads

Starburst, the data lake analytics platform, has announced the addition of Python support with PyStarburst and a new integration with the open source Python library Ibis.

This allows developers and data engineers to use a single, powerful MPP engine for both their analytical and transformation workloads, reducing the cost and complexity of their stack. With PyStarburst, users can write and run production-grade ETL pipelines and data transformations with a familiar syntax, making it easy to migrate existing PySpark and Snowpark pipelines to Starburst without rewriting code. The new Ibis integration provides a uniform Python API that can execute queries on more than 18 different engines, including DuckDB, pandas, PostgreSQL, and now Starburst Galaxy. Together, Ibis and Starburst Galaxy empower users to write portable Python code that executes on Starburst's high-performance data lake analytics engine, operating on data from more than 50 supported sources. This allows users to build analytic expressions across multiple data sources with reusable scripts that execute at any scale. The partnership between Voltron Data and Ibis was a natural fit for Starburst, as both companies share a commitment to openness and interoperability in the data ecosystem. To learn more about Starburst and its offerings, please visit