Databricks releases, every cloud
- Base environments are now supported on classic compute (Beta)
Manages Python dependencies using Databricks-provided or custom environments.
- Session restore for serverless jobs is in Public Preview
Restores Python variables and Spark session into a new notebook for debugging or exploration, requires eligible serverless compute job runs.
- Standard performance mode is now available for one-time runs in the Jobs API
Sets performance_target to STANDARD. Supports Apache Airflow's DatabricksSubmitRunOperator.
- Environment version 6 is now available
Supports serverless and standard classic compute.
- Write data back to Azure Databricks from Google Sheets
Writes to Unity Catalog tables, creating or overwriting them.
- Write data back to Databricks from Google Sheets
Creates or overwrites Unity Catalog tables from Google Sheets.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Manage project environments with %uv commands
Requires environment version 5 or above. Supports serverless notebooks.
- Session restore for serverless jobs is now in Beta
Restores Python variables and Spark session into a new notebook. Captures state snapshots on failure or long runs.
- JAR tasks on serverless compute are now generally available
Requires matching Scala, Java Development Kit, and Databricks Connect versions.
- Search and replace text across files
Works in Databricks Git folders or Declarative Automation Bundles projects from the Search pane.
- Filter updates for the Azure Databricks Excel Add-in
Supports cascading filters and case-insensitive string matching, replacing LIKE and IN filters.
- Filter updates for the Databricks Excel Add-in
Supports cascading filters and case-insensitive string matching, replaces LIKE and IN filters.
- Organize your work with spaces
Preserves open tabs for specific folders or projects.
- 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.
- Git CLI commands in Git folders are now in Public Preview
Enables standard Git commands like git stash and rebase in Databricks terminals. Requires workspace eligibility.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Mention Genie Code in notebook comments
Triggers AI help inline by typing @ and selecting Genie Code.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - July 6, 2026
Updates from Databricks Runtime 18, adds Spark Declarative Pipelines and IP address functions.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Workspace admin setting for serverless notebook execution timeout
Replaces manual override process, defaults to 2.5 hours.
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- Version 18.2
Adds CREATE OR REPLACE TEMP TABLE syntax and upgrades Snowflake JDBC driver to 3.28.0.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Faster package installs with %uv pip in serverless notebooks
Requires environment version 5 or above. Replaces %pip for faster installs.
- Native data profiling for notebook results tables
View column statistics by selecting headers and clicking Open selection details. Available in notebooks and new SQL editor.
- Workspace base environments are now generally available
Lets workspace admins create pre-built environments for serverless notebooks, enabled by default in compliance security profile workspaces.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Version 18.1
Supports DATETIMEOFFSET for Azure Synapse and adds schema evolution with INSERT statements.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Serverless compute now available for IRAP and Canada Protected B workloads on Azure Databricks
Requires environment version 5 to be enabled.
- Notebook tagging (Public Preview)
Organizes notebooks for easier management, supports governed tags for trust levels or lifecycle status.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Version 18.0
Upgrades Redshift JDBC driver to 2.1.0.28, adds SQL window functions to metric views.
- Serverless environment version 5 is now available
Includes CPU and GPU versions.
- Serverless compute now available for compliance standards
Adds HITRUST, PCI-DSS, TISAX, and UK Cyber Essentials Plus support.
- New GCP regions support serverless compute
Available in me-central1 and southamerica-east1 regions.
- Paste images into notebooks
Copies images from local file system using ⌘ + V or Ctrl + V.
- View and restore your recent workspace tab sessions
Restores up to 10 recent sessions.
- Serverless workspaces are now generally available
Come pre-configured with serverless compute and default storage.
- You can now use custom base environments for Python, Python Wheels, and notebook tasks in serverless jobs
Defined with YAML files, they support Python, Python wheel, and notebook tasks.
- View latest scheduled notebook job results
Shows latest scheduled run in notebooks and dashboards, can update notebook with latest results.
- Serverless compute is now available in Azure China North 3
Available for notebooks, jobs, pipelines, and SQL warehouses.
- Serverless workspaces are now available in new GCP regions
Available in most GCP regions, see documentation for list.
- Real-time collaboration in notebook cells, files, and SQL editor
Multiple users can edit the same cell simultaneously, viewing each other's edits.
- Serverless compute is now available in new regions
Added to Australia Southeast, Canada Central, Mexico Central, Norway East, and South Africa North regions.
- Use Git CLI commands in Git folders (Beta)
Runs standard Git commands in Databricks web terminal. Requires Git folder setup.
- JDBC Unity Catalog connection in Beta
Requires Databricks Runtime 17.3 or above. Available on standard, dedicated, or serverless compute.
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.