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May 2025

These features and Databricks platform improvements were released in May 2025.

note

Releases are staged. Your Databricks account might not be updated until a week or more after the initial release date.

Route optimization is available for serving endpoints​

May 30, 2025

You can now create route optimized serving endpoints for your model serving workflows to dramatically lower overhead latency and allow for substantial improvements in the throughput supported by your endpoint. See Route optimization on serving endpoints.

Improved UI for managing notebook dashboards​

May 30, 2025

Quickly navigate between a notebook and its associated dashboards by clicking Dashboard icon. in the top right.

See Navigate between a notebook dashboard and a notebook.

SQL authoring improvements​

May 30, 2025

The following improvements were made to the SQL editing experience in the SQL editor and notebooks:

  • Filters applied to result tables now also affect visualizations, enabling interactive exploration without modifying the underlying query or dataset. To learn more about filters, see Filter results.
  • In a SQL notebook, you can now create a new query from a filtered results table or visualization. See Create a query from filtered results.
  • You can hover over * in a SELECT * query to expand the columns in the queried table.
  • Custom SQL formatting settings are now available in the new SQL editor and the notebook editor. Click View > Developer Settings > SQL Format. See Customize SQL formatting.

Metric views are in Public Preview​

May 29, 2025

Unity Catalog metric views provide a centralized way to define and manage consistent, reusable, and governed core business metrics. They abstract complex business logic into a centralized definition, enabling organizations to define key performance indicators once and use them consistently across reporting tools like dashboards, Genie spaces, and alerts. Use a SQL warehouse running on the Preview channel (2025.16) or other compute resource running Databricks Runtime 16.4 or above to work with metric views. See Unity Catalog metric views.

Workspaces system table now available (Public Preview)​

May 28, 2025

You can now use the system.access.workspaces_latest table to monitor the latest state of all active workspaces in your account.

Join this table with other system tables to analyze reliability, performance, and cost across your account's workspaces. See Workspaces system table reference.

Claude Sonnet 4 and Claude Opus models now available on Mosaic AI Model Serving​

May 27, 2025

The Anthropic Claude Sonnet 4 and Anthropic Claude Opus 4 models are now available in Mosaic AI Model Serving as Databricks-hosted foundation models.

These models are available using Foundation Model APIs pay-per-token in US regions only.

New alerts in Beta​

May 22, 2025

A new version of Databricks SQL alerts is now in Beta. You can use alerts to periodically run queries, evaluate defined conditions, and send notifications if a condition is met. This version simplifies creating and managing alerts by consolidating query setup, conditions, schedules, and notification destinations into a single interface. You can still use legacy alerts alongside the new version. See Databricks SQL alerts.

Dashboards, alerts, and queries are supported as workspace files​

May 20, 2025

Dashboards, alerts, and queries are now supported as workspace files, which means you can programmatically interact with these Databricks objects like any other file, from anywhere the workspace filesystem is available. See What are workspace files? and Programmatically interact with workspace files.

Pipelines system table is now available (Public Preview)​

May 20, 2025

The system.lakeflow.pipelines table is a slowly changing dimension table (SCD2) that tracks all pipelines created in your Databricks account.

See Pipelines table schema.

Databricks on Google Cloud supports cross-cloud read access to AWS S3 storage​

May 20, 2025

Use Unity Catalog to access and govern all of your S3 data from within a secure Databricks on Google Cloud environment. There is no need to migrate or copy datasets. Access to S3 is read-only.

See Create a storage credential for connecting to AWS S3 (read-only).

Mosaic AI Model Serving now available in europe-west3​

May 19, 2025

Mosaic AI Model Serving is now available in europe-west3.

Databricks Asset Bundles in the workspace (Public Preview)​

May 19, 2025

Collaborating on Databricks Asset Bundles with other users in your organization is now easier with bundles in the workspace, which allows workspace users to edit, commit, test, and deploy bundle updates through the UI.

See Collaborate on bundles in the workspace.

Workflow task repair now respects transitive dependencies​

May 19, 2025

Previously, repaired tasks were unblocked once their direct dependencies completed. Now, repaired tasks wait for all transitive dependencies. For example, in a graph A → B → C, repairing A and C will block C until A finishes.

Serverless compute is now available in europe-west3​

May 14, 2025

Workspaces in europe-west3 are now eligible to use serverless compute. This includes serverless SQL warehouses and serverless compute for notebooks, jobs, and DLT. See Connect to serverless compute.

Databricks Apps (Generally Available)​

May 13, 2025

Databricks Apps is now generally available (GA). This feature lets you build and run interactive full-stack applications directly in the Databricks workspace. Apps run on managed infrastructure and integrate with Delta Lake, notebooks, ML models, and Unity Catalog.

See Databricks Apps.

Databricks Runtime 16.4 LTS is GA​

May 13, 2025

Databricks Runtime 16.4 and Databricks Runtime 16.4 ML are now generally available.

See Databricks Runtime 16.4 LTS and Databricks Runtime 16.4 LTS for Machine Learning.

Databricks JDBC driver 2.7.3​

May 12, 2025

The Databricks JDBC Driver version 2.7.3 is now available for download from the JDBC driver download page.

This release includes the following enhancements and new features:

  • Added support for Azure Managed Identity OAuth 2.0 authentication. To enable this, set the Auth_Flow property to 3.
  • Added support for OAuth Token exchange for IDPs different than host. OAuth access tokens (including BYOT) will be exchanged for a Databricks access token.
  • OAuth browser (Auth_Flow=2) now supports token caching for Linux and Mac operating systems.
  • Added support for VOID, Variant, and TIMESTAMP_NTZ data types in getColumns() and getTypeInfo() APIs.
  • The driver now lists columns with unknown or unsupported types and maps them to SQL VARCHAR in the getColumns() metadata API.
  • Added support for cloud.databricks.us and cloud.databricks.mil domains when connecting to Databricks using OAuth (AuthMech=11).
  • Upgraded to netty-buffer 4.1.119 and netty-common 4.1.119 (previously 4.1.115).

This release resolves the following issues:

  • Compatibility issues when deserializing Apache Arrow data with Java JVMs version 11 or higher.
  • Issues with date and timestamp before the beginning of the Gregorian calendar when connecting to specific Spark versions with Arrow result set serialization.

For complete configuration information, see the Databricks JDBC Driver Guide installed with the driver download package.

Updated lineage system tables schema​

May 11, 2025

The lineage system tables (system.access.column_lineage and system.access.table_lineage) have been updated to better log entity information.

  • The entity_metadata column replaces entity_type, entity_run_id, and entity_id, which have been deprecated.
  • The record_id column is a new primary key for the lineage record.
  • The event_id column logs an identifier for lineage event, which can be shared by multiple rows if they were generated by the same event.
  • The statement_id column logs the query statement ID of the query that generated the lineage event. It is a foreign key that can be joined with the system.query.history table.

For a full schema of these tables, see Lineage system tables reference.

Query snippets are now available in the new SQL editor, notebooks, files, and dashboards​

May 9, 2025

Query snippets are segments of queries that you can share and trigger using autocomplete. You can now create query snippets through the View menu in the new SQL editor, and also in the notebook and file editors. You can use your query snippets in the SQL editor, notebook SQL cells, SQL files, and SQL datasets in dashboards.

See Query snippets.

You can now create views in ETL pipelines​

May 8, 2025

The CREATE VIEW SQL command is now available in ETL pipelines. You can create a dynamic view of your data. See CREATE VIEW (Lakeflow Declarative Pipelines).

Configure Python syntax highlighting in Databricks notebooks​

May 8, 2025

You can now configure Python syntax highlighting in notebooks by placing a pyproject.toml file in the notebook's ancestor path or your home folder. Through the pyproject.toml file, you can configure ruff, pylint, pyright, and flake8 linters, as well as disable Databricks-specific rules. This configuration is supported for clusters running Databricks Runtime 16.4 or above, or Client 3.0 or above.

See Configure Python syntax highlighting.

Jobs and pipelines now share a single, unified view (Public Preview)​

May 7, 2025

You can now view all workflows, including jobs, ETL pipelines, and ingestion pipelines, in a single unified list. See View jobs and pipelines.

Predictive optimization enabled for all existing Databricks accounts​

May 7, 2025

Starting May 7, 2025, Databricks enabled predictive optimization by default for all existing Databricks accounts. This will roll out gradually based on your region and will be completed by July 1, 2025. When predictive optimization is enabled, Databricks automatically runs maintenance operations for Unity Catalog managed tables. For more information on predictive optimization, see Predictive optimization for Unity Catalog managed tables.

File events for external locations improve file notifications in Auto Loader and file arrival triggers in jobs (Public Preview)​

May 5, 2025

You can now enable file events on external locations that are defined in Unity Catalog. This makes file arrival triggers in jobs and file notifications in Auto Loader more scalable and efficient.

This feature is in Public Preview. Auto Loader support for file events requires enablement by a Databricks representative. For access, reach out to your Databricks account team.

For details, see the following:

Mosaic AI Vector Search is now generally available​

May 5, 2025

Mosaic AI Vector Search is now generally available. See Mosaic AI Vector Search.

Mosaic AI Model Serving is now generally available​

May 5, 2025

Mosaic AI Model Serving is now generally available in the following regions: asia-south1, asia-southeast1, europe-west2, us-west1, us-east4, us-east1 and us-central1.

Mosaic AI Model Serving provides a unified interface to deploy, govern, and query AI models. Each model you serve is available as a REST API to integrate into your web or client application.

See Deploy models using Mosaic AI Model Serving.

Mosaic AI Model Serving region expansion​

May 5, 2025

Mosaic AI Model Serving is now available in the following regions:

  • asia-south1
  • asia-southeast1
  • europe-west2
  • us-east4
  • us-west1

See Model serving regional availability.

The jobs system tables (Public Preview) are enabled by default​

May 1, 2025

The system.lakeflow schema, which contains system tables related to jobs, is now enabled by default in all Unity Catalog workspaces. See Jobs system table reference.

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