Databricks releases, every cloud
- Base environments are now supported on classic compute (Beta)
Manages Python dependencies using Databricks-provided or custom environments.
- Genie Code adds conversation controls
Lets you fork conversations, use /btw for side questions, and edit earlier messages.
- Git Folder Serverless is in Beta
Shares serverless compute and pyproject.toml environment across notebooks and files.
- Automatic change data feed is now generally available
Requires Databricks Runtime 19 or above with row tracking enabled. Makes MERGE and UPDATE operations about 15% faster.
- Databricks Runtime 19: September 1, 2026
Replaces manual change data feed enablement, requires row tracking enabled.
- Databricks Runtime maintenance updates (09/01)
Includes bug fixes, security patches, and performance improvements for versions 13.3 to 18.2.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Genie Code scheduled tasks are now generally available
Runs prompts on a recurring schedule, producing a continuable Genie chat with results.
- Genie Code scheduled tasks will soon be available by default for workspaces with the compliance security profile enabled Coming soon
Replaces manual runs of recurring analysis tasks. Available in October 2026.
- Genie Code for AI Runtime (Public Preview)
Generates distributed training code and resolves environment issues. Requires AI Runtime.
- Genie Code is now available as a Lakeflow Jobs task (Beta)
Runs prompts autonomously, reading upstream outputs and calling tools as needed, returning a conversation link.
- Default Python package repositories are GA for Lakeflow pipelines and classic compute
Supports private or authenticated registries as workspace defaults. Applies to UI and API created classic compute.
- Choose an effort level in Genie Code
Sets balance between response quality and cost, defaults to Auto for highest quality.
- Manage project environments with %uv commands
Requires environment version 5 or above. Supports serverless notebooks.
- Genie Code supports file uploads
Uploads are used as chat context, see Attach files for details.
- Custom trace views in the MLflow trace explorer are in Beta
Genie generates views based on plain language descriptions, surfacing relevant trace fields and metrics.
- Target an Azure capacity reservation group for classic compute
Requires VNet injection, guarantees compute capacity for constrained VM types.
- Genie Code web search is in Beta
Searches the public web for current info, disabled by default.
- Databricks Runtime maintenance updates (08/04)
Includes bug fixes, security patches, and performance improvements for versions 13.3 to 18.2.
- Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
- Full page Genie Code is now generally available
Runs multiple chats in parallel, with notebooks and files as tabs.
- Serverless compute access control is now generally available
Governs access to notebooks, jobs, and pipelines through Default Interactive and Automated Compute objects. Existing workloads run unchanged.
- Web terminal on serverless GPU compute (AI Runtime) is in Public Preview
Runs shell commands, monitors GPU usage, and manages files on serverless GPU compute. Requires environment version 5 or above.
- Databricks Runtime maintenance updates (07/24)
Includes bug fixes, security patches, and performance improvements for versions 13.3 to 18.2.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Dedicated group clusters will soon be available by default for workspaces with the compliance security profile enabled Coming soon
Enables shared compute for groups with compliance security profile, supporting Databricks Runtime for ML and RDD APIs.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18 and Databricks Runtime 18 for Machine Learning have transitioned to LTS
Receives 3 years of stability and security fixes.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 19 and Databricks Runtime 19 for Machine Learning are now generally available
Powered by Apache Spark 4.2.0.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 19: July 23, 2026
Enables Arrow-optimized Python UDFs by default, changing type-coercion behavior.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Genie Code scheduled tasks are in Beta
Runs prompts on a recurring schedule, producing a continuable Genie chat with results.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - MLflow trace storage in Unity Catalog is now generally available
Stores traces in OpenTelemetry format with unlimited storage and SQL query access.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Serverless compute is now available in the Azure UK West region
Supports notebooks, jobs, pipelines, and SQL warehouses, with private connectivity.
- Databricks Runtime maintenance updates (06/29)
Includes bug fixes, security patches, and performance improvements for versions 13.3 to 18.2.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 19 (Beta): June 26, 2026
Restricts environment variables and Spark configurations in standard access mode. Removes previously allowed settings.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Genie Code system table now counts only user-submitted interactions
Excludes background and automated requests, such as autocomplete and quick-fix suggestions.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 19 and Databricks Runtime 19 for Machine Learning are in Beta
Powered by Apache Spark 4.2.0.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 19 (Beta): June 15, 2026
Replaces JDK 17 with JDK 21, removes 90 Python packages.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Genie Code now uses models served through OpenAI on Databricks
Adds OpenAI to existing Azure OpenAI and Anthropic models.
- Databricks Runtime 18: June 10, 2026
Adds Spark Declarative Pipelines and IP address functions, requires no changes to existing setups.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Schedule deferred policy enforcement for all-purpose compute
Applies on next restart or immediately, and admins can cancel scheduled enforcements.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18: June 8, 2026
Adds NEAREST BY SQL join type and DESCRIBE TABLE PARTITION for v2 catalog tables.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18: June 4, 2026
NATURAL JOIN now matches columns case-insensitively by default. Set spark.sql.legacy.naturalJoinCaseSensitiveColumnMatching to true to restore previous behavior.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18: May 29, 2026
Treats NaN values as duplicates, preserves Unity Catalog foreign table permissions during metadata refresh.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
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.