Databricks releases, every cloud
- Jira connector (Beta)
Ingests Jira issues, comments, and attachments metadata into Databricks.
- Microsoft Dynamics 365 connector (Public Preview)
Ingests data from Dynamics 365 apps into Databricks. Requires Lakeflow Connect.
- NetSuite connector (Public Preview)
Ingests data from NetSuite2.com via API, CLI, or notebook.
- Databricks Runtime 18.0 and Databricks Runtime 18.0 ML are in Beta
Powered by Apache Spark 4.1.0, includes JDK 21 as default.
- Databricks Runtime maintenance updates (12/09)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 17.3.
- ForEachBatch for Spark Declarative Pipelines on Lakeflow is available (Public Preview)
Allows processing streams as micro-batches in Python. Requires Lakeflow setup.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Spark Declarative Pipelines on Lakeflow stream progress metrics are generally available
Supports querying event log for stream progress metrics.
- Configure full refresh behavior for managed database connectors
Applies to Lakeflow Connect managed database connectors, allowing scheduled full refresh snapshots and automatic recovery from unsupported schema changes.
- Databricks SQL version 2025.35 is rolling out in Current
Includes new features, see documentation for details.
- Databricks Runtime maintenance updates (11/18)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 17.3.
- Jobs can now be triggered on source view update
Supports views referencing supported table types, see documentation for specifics.
- Databricks SQL alerts are now in Public Preview
Offers a new editing experience, replacing the previous version.
- Improved full refresh flow for managed database connectors
Reduces downtime by delaying table refresh until snapshot completion, minimizing PENDING_RESET errors.
- Convert foreign tables to Unity Catalog managed or external tables (Public Preview)
Requires Databricks Runtime 17.0 LTS or above. Uses ALTER TABLE SET MANAGED or SET EXTERNAL.
- SFTP connector (Public Preview)
Extends Auto Loader to ingest files from SFTP servers.
- Lakeflow Declarative Pipelines has been renamed to Lakeflow Spark Declarative Pipelines
Replaces Lakeflow Declarative Pipelines, see Spark Declarative Pipelines for details.
- SQL Editor visualization fix
Tooltips now display in front of the legend.
- Databricks Runtime maintenance updates (11/04)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 17.3.
- Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
- JAR tasks are now supported on serverless compute
Run JAR jobs without a cluster.
- Salesforce ingestion connector supports history tracking (SCD type 2)
Enables history tracking, overwriting default SCD type 1 behavior.
- Databricks SQL version 2025.35 is now available in Preview
Adds EXECUTE IMMEDIATE constant expressions and LIMIT ALL for recursive CTEs.
- Zerobus Ingest connector in Lakeflow Connect (Public Preview)
Enables record-by-record ingestion into Delta tables via gRPC API.
- Databricks Runtime 17.3 LTS is now GA
Replaces 7.3 LTS, requires Databricks account.
- Databricks Runtime maintenance updates (10/21)
Includes bug fixes, security patches, and performance improvements.
- New alert editing experience
Replaces old editor with a multi-tab editor for unified workflow.
- Unified runs list (Public Preview)
Combines job and pipeline runs into one list.
- Jobs can now be triggered on source table update
Triggers require Databricks Runtime 7.0 or later.
- Create backfill job runs
Triggers job runs to load past data, useful for repairing processing failures.
- Visualizations fix
Fixes legend selection for charts with aliased series names in SQL editor and notebooks.
- Databricks Runtime maintenance updates (10/07)
Includes bug fixes, security patches, and performance improvements.
- Databricks Runtime 17.3 LTS and Databricks Runtime 17.3 LTS ML are in Beta
Powered by Apache Spark 4.0.0, includes new configuration options.
- Semantic metadata in metric views
Requires YAML 1.1 and Databricks Runtime 17.3 or higher.
- Lakeflow Pipelines Editor is now in public preview
Replaces multi-file editor, edits pipelines as files in asset browser, defaults to Python and SQL code.
- New requirement to create connections for Salesforce ingestion
Requires Databricks connected app installed. Applies to new connections only.
- Databricks SQL version 2025.30 is now available in Preview
Adds LIKE operator support for UTF8 collations and ST_ExteriorRing function.
- Databricks Runtime maintenance updates
Includes bug fixes, security patches, and performance improvements.
- Migrate Spark Declarative Pipelines on Lakeflow pipelines from legacy publishing mode is generally available
Replaces legacy mode that only published to a single catalog and schema. Now supports multiple catalogs and schemas.
- Databricks Runtime 17.2 is now is now GA
Replaces 7.3 and earlier, requires new cluster creation.
- Discover files in Auto Loader efficiently using file events without enrollment (Public Preview)
Requires file events enabled on external locations.
- Google Analytics Raw Data connector GA
Enables ingestion of raw Google Analytics data into Databricks, requires Google Analytics 4 and Google BigQuery setup.
Headlines, dates and product areas are Databricks' own, and every item links to the note it came from. The one-line summaries are ours.