Starburst Enterprise 427-e STS

• Starburst Enterprise now supports the PyStarburst library, allowing for client connections to SEP using the Python DataFrame API. This powerful new tool allows data engineers to build complex data pipelines and migrate existing PySpark and Snowpark workloads to SEP. To learn more about using Python as a client tool with Starburst Enterprise, read our documentation.
  

  Example of a data transformation written in Python

• We’re continuing to build Starburst Enterprise as the ideal query engine for the data lake. To further build optionality for our customers, we’ve added public preview support for Databricks Unity Catalog as a metastore for Delta Lake. To learn more, read the Delta Lake connector documentation.

In addition to these enterprise enhancements, all features added in the Trino 427 release are included as well. Here are some of the highlights from this release:

• Improved performance for GROUP BY and DISTINCT.
• Support for pushing down UPDATE statements into connectors.
• Support for reading Delta Lake tables with Deletion Vectors.
• Faster writing to Parquet files in Delta Lake and Iceberg.
• Support for querying tags in Iceberg.

For the complete list of features, changes, and fixes in this latest SEP release, read the release notes for 427-e.