Latest releases from the Databricks ecosystem.

Unity Catalog AI 0.4.0

DatabricksFunctionClient now supports an optional warehouse_id for function execution, enabling use in workspaces without serverless compute. Python 3.10+ is now required, and several bug fixes address issues with Gemini toolkit, LangGraph, and OSS client function creation.

UnityCatalog 0.4.1

The Unity Catalog Spark connector now supports atomic REPLACE TABLE AS SELECT and Dynamic Partition Overwrite for managed Delta tables, and introduces a credential-scoped file system to prevent out-of-memory errors. A critical security fix addresses a JWT issuer validation bypass, requiring new server configuration properties for existing deployments with authorization enabled.

UnityCatalog 0.4.0

Unity Catalog now supports managing AWS storage credentials and external locations directly, enabling secure, temporary access to S3 data for Databricks workloads. Credential renewal is now enabled by default for Spark jobs, and atomic CTAS operations are introduced for Delta tables, improving data reliability.

UnityCatalog 0.3.1

The Unity Catalog Spark connector now supports automatic credential renewal for S3, Azure, and GCS, and introduces OAuth authentication for seamless token management. This release also adds experimental support for UC-managed Delta tables, where Unity Catalog coordinates storage and commits.

UnityCatalog 0.3.0

Unity Catalog now supports Spark 4.0 and Delta Lake 4.0, enhancing compatibility with the latest Databricks runtime components. New API surfaces for credentials and external locations provide more flexible handling of external storage services.

Unity Catalog AI 0.3.1

The Unity Catalog AI 0.3.1 release improves function client defaults, enhancing SQL NULL handling and connection recovery for DatabricksFunctionClient. It also optimizes Spark session management and provides clearer error messages for Pydantic validation issues.

Unity Catalog AI 0.3.0

Functions now execute in a safer sandboxed process by default, with a new local development mode for easier debugging. You can now retrieve UC-registered Python functions as direct Python callables or their source code, and DatabricksFunctionClient connection reliability has improved.

Unity Catalog AI 0.2.0

This release introduces new integrations for Gemini and LiteLLM, enabling Unity Catalog functions as tools for these models. The Databricks client now exclusively supports serverless endpoints, adds new APIs for function wrapping, and includes support for `requirements`, `environment_version`, and `Variant` types.

Unity Catalog AI 0.1.0

This initial release introduces Unity Catalog AI, providing a core client for managing and executing Unity Catalog functions as GenAI tools. It includes integration packages for popular AI frameworks like LangChain, LlamaIndex, OpenAI, Anthropic, CrewAI, and AutoGen, enabling seamless use of UC functions within these applications.

Unity Catalog 0.2.1

This release introduces a new Python client for Unity Catalog and adds support for the MODIFY permission on tables, allowing non-owners to write data. It also includes UI improvements for models and general usability, alongside better Iceberg catalog API compatibility.