Databricks releases, every cloud
- 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.
- 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.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- 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.
- 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.
- 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.
- 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.
- Python custom data sources can be used with Spark Declarative Pipelines on Lakeflow
Supports Python custom data sources and sinks in pipeline definitions.
- Spark Declarative Pipelines on Lakeflow now supports stream progress metrics in Public Preview
Supports querying event log for stream progress metrics.
- Migrate Spark Declarative Pipelines on Lakeflow from legacy publishing mode is rolled back to Public Preview
Reverts migration feature to Public Preview due to issues. Requires re-enabling default publishing mode in pipelines.
- Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
- SQL Server connector supports SCD type 2
Maintains a history of changes, rather than overwriting outdated records.
- Default warehouse setting is now available in Beta
Applied across SQL editor, AI/BI dashboards, and other tools, with optional user override.
- Migrate Spark Declarative Pipelines on Lakeflow from legacy publishing mode is now GA
Replaces legacy single-catalog publishing with multi-catalog support.
- Microsoft SQL Server connector GA
Replaces manual ingestion scripts, requires Lakeflow Connect setup.
- Databricks SQL version 2025.25 is rolling out in Current
Rolls out from August 20th to August 28th, 2025.
- Set the run-as user for Spark Declarative Pipelines on Lakeflow
Replaces user accounts with a service principal for automated workloads.
- Databricks SQL version 2025.25 is now available in Preview
Adds recursive common table expressions and spatial SQL expressions.
- Fixed timeout handling for materialized views and streaming tables
New views and tables apply warehouse timeout, existing ones require CREATE OR REFRESH. Default timeout is 2 days.
- New SQL editor is generally available
Provides a unified authoring environment with features like real-time collaboration and enhanced Databricks Assistant integration.
- Spark Declarative Pipelines on Lakeflow template in bundles in the workspace (Public Preview)
Creates ETL pipelines in workspace bundles using Lakeflow template. Requires New ETL pipeline setup.
- Jobs in continuous mode can now have task-level retries for failed tasks
Task-level retries replace job-level retries, require continuous mode.
- ServiceNow connector GA
Replaces manual API configuration, requires Lakeflow Connect setup.
- Preset date ranges for parameters in the SQL editor
Includes options like This week, Last 30 days, and Last year for timestamp and date parameters.
- Jobs & Pipelines list now includes Databricks SQL pipelines
Includes materialized views and streaming tables created with Databricks SQL.
- Inline execution history in SQL editor
Shows past results without re-executing queries, links to past query profiles.
- Moving tables between Spark Declarative Pipelines on Lakeflow pipelines is now GA
Supports moving tables in Unity Catalog ETL pipelines.
- Databricks SQL version 2025.20 is now available in Current
Rolls out in stages to the Current channel, see 2025.20 features for details.
- SQL editor updates
Supports date-range and multi-select parameters, and rearranges the run button and catalog picker to the header.
- Git support for alerts
Tracks alert changes, requires placing alerts in a Databricks Git folder. Newly cloned alerts are paused.
- Parent tasks (Run job and For each) now have a separate limit
Separate limit doesn't count against overall limit, see Resource limits.
- Databricks SQL version 2025.20 is now available in Preview
Includes new features and behavioral changes in Preview channel.
- Databricks SQL Serverless engine upgrades
Upgrades bring up to 25% lower latency and add Predictive Query Execution and Photon vectorized shuffle.
Headlines, dates and product areas are Databricks' own, from the release notes published for each cloud, and every item links to the note it came from. The one-line summaries are ours. Not a Databricks product and not affiliated with Databricks, Inc.