Databricks releases, every cloud
- Databricks SQL pipelines support notifications and performance mode (Beta)
Supports failure notifications and serverless performance mode for materialized views and streaming tables.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18: March 10, 2026
Includes clearer error messages for scalar subqueries and operating system security updates.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime maintenance updates (03/10)
Includes bug fixes, security patches, and performance improvements for versions 13.3 to 18.0.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Workday HCM connector (Beta)
Ingests Workday Human Capital Management data into Databricks.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18: February 26, 2026
Adds SET and UNSET METADATA ON COLUMN SQL commands for Unity Catalog table columns. Includes OS security updates.
- Databricks Runtime maintenance updates (02/26)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 18.0.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Change to use_case field in VPC endpoint API responses Coming soon
Changes from WORKSPACE_ACCESS to GENERAL_ACCESS, see API docs for details.
- COMMENT ON streaming tables is now GA
Adds comments to streaming tables, previously only available for non-streaming tables.
- Databricks SQL version 2025.40 is rolling out in Current
Replaces version 2025.39, requires no setup changes.
- JAR tasks on serverless compute is now in Public Preview
Allows running JAR jobs without a cluster.
- Databricks Runtime 18: February 19, 2026
Inferencing Excel string cells now respects cell type, updating from auto-casting to narrower types.
- Databricks Runtime maintenance updates (02/19)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 18.0.
- TikTok Ads connector (Beta)
Ingests data from TikTok Ads into Databricks.
- Databricks Runtime 18.1 and Databricks Runtime 18.1 ML are in Beta
Powered by Apache Spark 4.1.0.
- File events enabled by default on new external locations
Enabled on new locations, detects file changes for storage jobs and pipelines, can be disabled after creation.
- HubSpot connector (Beta)
Ingests HubSpot Marketing Hub data into Databricks via Lakeflow Connect.
- Configure default Python package repositories for Spark Declarative Pipelines on Lakeflow (Public Preview)
Allows installation from internal Python repositories without index-url or extra-index-url. Requires workspace admin configuration.
- Databricks SQL version 2025.40 is now available in Preview
Adds SQL scripting with procedural logic and expands parameter markers and IDENTIFIER clause support.
- Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
- Applying filters, masks, tags, and comments to pipeline-created datasets is now GA
Modifies ETL and ingestion pipelines using CREATE, ALTER, or Lakeflow UI. Applies to Spark Declarative Pipelines on Lakeflow and Lakeflow Connect.
- Google Ads connector (Beta)
Ingests data from Google Ads into Databricks via Lakeflow Connect.
- Zendesk Support connector (Beta)
Ingests ticket, help center, and community forum data from Zendesk Support.
- Trigger on update for pipelines (GA)
Refreshes pipeline when source table changes, usable in Databricks SQL pipeline schedules.
- View and restore your recent workspace tab sessions
Restores up to 10 recent sessions.
- Databricks Runtime 18: January 27, 2026
Reports batchSize and file processing metrics, renames spark.sql.xml.legacyXMLParser.enabled config property.
- Databricks Runtime maintenance updates (01/27)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 18.0.
- Google Drive connector (Beta)
Supports read_files, spark.read, COPY INTO, and Auto Loader for ingesting files.
- Databricks Runtime 18: January 15, 2026
Uses JDK 21, replacing JDK 17, with changes to Double and Float string representations.
- Databricks Runtime 18.0 is now GA
Replaces Databricks Runtime 7.3.
- Ingest Salesforce formula fields incrementally (Beta)
Replaces snapshotting with incremental ingestion, improving performance and reducing costs.
- Row filtering for managed ingestion connectors (Beta)
Applies conditions like a SQL WHERE clause, available for Google Analytics, Salesforce, and ServiceNow connectors.
- Databricks Runtime maintenance updates (01/09)
Includes bug fixes, security patches, and performance improvements for versions 12.2 to 17.3.
- Meta Ads connector (Beta)
Ingests data from Meta Ads, requires setup as a data source.
- MySQL connector in Lakeflow Connect (Public Preview)
Enables incremental data ingestion from various MySQL databases. Requires access request through account team.
- Updated Lakeflow Jobs UI is generally available
Simplifies job creation and editing, see Lakeflow Jobs for details.
- Confluence connector (Beta)
Ingests Confluence spaces and pages into Databricks, requires OAuth U2M configuration.
- PostgreSQL connector in Lakeflow Connect (Public Preview)
Enables incremental data ingestion from various PostgreSQL databases. Requires configuration.
- Change owner for materialized views or streaming tables defined in Databricks SQL
Done through Catalog Explorer, replacing previous methods.
- Customizable SharePoint connector (Beta)
Ingests structured, semi-structured, and unstructured files into Delta tables with customizable schema inference and parsing options.
- Discover files in Auto Loader efficiently using file events
Requires file events enabled on external locations. Replaces directory listing for efficiency.
- Jira connector (Beta)
Ingests Jira issues, comments, and attachments metadata into Databricks.
Headlines, dates and product areas are Databricks' own, and every item links to the note it came from. The one-line summaries are ours.