Databricks releases, every cloud
- Base environments are now supported on classic compute (Beta)
Manages Python dependencies using Databricks-provided or custom environments.
- 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.
- 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.
- Manage project environments with %uv commands
Requires environment version 5 or above. Supports serverless notebooks.
- Target an Azure capacity reservation group for classic compute
Requires VNet injection, guarantees compute capacity for constrained VM types.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Serverless compute is now available in the Azure UK West region
Supports notebooks, jobs, pipelines, and SQL warehouses, with private connectivity.
- 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) - 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) - Reorganized Spark Declarative Pipelines on Lakeflow documentation
Conceptual topics are now under Concepts.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Genie Code now supports auto-approve for tool actions
Approves tool actions without prompts, using an AI classifier to block risky ones.
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.
- Databricks Container Services for standard compute is now available (Beta)
Requires Databricks Runtime 18.3 or later, allows custom Docker images in shared compute.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - 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.
- 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) - Workspace skills for Genie Code are now available
Workspace admins can create shared skills for machine learning pipelines and domain-specific processes.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Documentation site table of contents tabs
Replaces static sidebar with tabbed navigation, includes 6 context tabs.
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- Databricks Assistant is now Genie Code
Adds autonomous multi-step data tasks, replaces Databricks Assistant.
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.
- 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.
- Change to use_case field in VPC endpoint API responses Coming soon
Changes from WORKSPACE_ACCESS to GENERAL_ACCESS, see API docs for details.
- Serverless compute now available for compliance standards
Adds HITRUST, PCI-DSS, TISAX, and UK Cyber Essentials Plus support.
- Connect Databricks Assistant to MCP servers
Connects to external tools and data sources through MCP servers, requiring permission to use added servers.
- Partner-powered AI features are now supported in the Canada, Brazil, and United Kingdom Azure Geographies
Uses models hosted in the same Azure Geography as the workspace, requires cross-geo processing for some features.
- New GCP regions support serverless compute
Available in me-central1 and southamerica-east1 regions.
- 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.
- Create skills for Databricks Assistant
Extends Databricks Assistant with domain-specific tasks, following the open Agent Skills standard.
- 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.
- Serverless compute is now available in new regions
Added to Australia Southeast, Canada Central, Mexico Central, Norway East, and South Africa North regions.
- Serverless notebook tasks can now use jobs environment
Replaces inherited serverless environment with configurable job environment.
- Databricks Assistant Agent mode can now use models served through Anthropic on Databricks
Requires partner-powered AI features to be enabled. Uses endpoints hosted by Databricks.
- Serverless compute has been updated to version 17.3
Updated from version 17.2, requires no configuration changes.
- Configure compute to use AWS Capacity Blocks
Replaces on-demand instances, requires AWS account setup.
- The billable usage table now records the performance mode of serverless jobs and pipelines
Records performance mode in product_features.performance_target column with values PERFORMANCE_OPTIMIZED, STANDARD, or null.
- The Data Science Agent can now also use models served through Anthropic on Databricks
Uses models served through Anthropic when partner-powered AI features are enabled. Requires partner-powered AI features to be enabled.
- Notebook improvements
Cell execution minimap appears in right margin, supports up to 100MB notebooks.
- Databricks Assistant integrated with compute
Creates compute resources, pools, and policies, and answers questions about them. Available on some compute pages.
Headlines, dates and product areas are Databricks' own, and every item links to the note it came from. The one-line summaries are ours.