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.
- 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.
- 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.
- Search and replace text across files
Works in Databricks Git folders or Declarative Automation Bundles projects from the Search pane.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Organize your work with spaces
Preserves open tabs for specific folders or projects.
- 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) - 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) - Customer-managed keys now support MLflow managed evaluation features
Supports MLflow 3 scorers and requires non-CMK encrypted catalog.
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.
- MLflow trace storage in Unity Catalog is now in Public Preview
Stores OpenTelemetry traces, governed by Unity Catalog permissions, queryable from Databricks SQL or MLflow Python SDK.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - 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) - 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.
- Store and query MLflow traces in Unity Catalog (Beta)
Stores MLflow traces in Delta tables for long-term retention and analysis using OpenTelemetry format.
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- View latest scheduled notebook job results
Shows latest scheduled run in notebooks and dashboards, can update notebook with latest results.
- Real-time collaboration in notebook cells, files, and SQL editor
Multiple users can edit the same cell simultaneously, viewing each other's edits.
- Use Git CLI commands in Git folders (Beta)
Runs standard Git commands in Databricks web terminal. Requires Git folder setup.
- Databricks Assistant Agent mode: Data Science Agent is in Beta
Orchestrates multi-step workflows from a single prompt, building entire notebooks for tasks like EDA and machine learning.
- Admins can now manage a workspace's serverless base environments (Public Preview)
Defines custom environment specs for serverless notebooks, allows setting a default for new notebooks.
- Track and navigate notebook runs with the new cell execution minimap
Appears in the right margin, shows cell execution states, and allows clicking to jump to a cell.
- Enhanced autocomplete for complex data types in notebooks
Supports structs, maps, and arrays in SQL cells, and provides column recommendations for CTEs using SELECT *.
- Serverless compute runtime updated to 17.1
corresponds to Databricks Runtime 17.1, see release notes for details.
- Databricks Assistant: User and workspace instructions now available
Custom instructions can be added by users or admins, applying to all Assistant experiences.
- Edit mode in Assistant does multi-cell code refactoring and more
Performs reasoning and editing across multiple cells without manual intervention.
- Serverless compute runtime updated to 17.0
corresponds to Databricks Runtime 17.0, see release notes for details
- Improvements to the notebook editing experience
Adds split view and native find-and-replace tool.
- Serverless notebooks: Restore Python variables after idle termination
Restores Python variables from snapshot after idle termination. Requires reconnection to restore.
- Serverless compute is now available in northamerica-northeast1, europe-west1, and asia-northeast1
Supports notebooks, workflows, and Lakeflow pipelines.
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.