Databricks releases, every cloud
- 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.
- Genie Code for AI Runtime (Public Preview)
Generates distributed training code and resolves environment issues. Requires AI Runtime.
- JAR tasks on serverless compute are now generally available
Requires matching Scala, Java Development Kit, and Databricks Connect versions.
- 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.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Protobuf tensor input for custom model serving endpoints (Public Preview)
Replaces JSON with serialized KServe v2 ModelInferRequest. Requires endpoints deployed after July 9, 2026.
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) - Custom Docker images for AI Runtime CLI workloads (Beta)
Allows custom system library versions and complex dependencies, requires setup via Use custom Docker images.
- AI Runtime CLI (Beta)
Submits and manages distributed training workloads on serverless GPU compute from a local machine.
- Workspace admin setting for serverless notebook execution timeout
Replaces manual override process, defaults to 2.5 hours.
- Serve custom LLMs with Custom Model Serving (Beta)
Supports multimodal models and PEFT recipes, unlike Foundation Model APIs.
- 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.
- 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) - AI Runtime 1xH100 accelerator (Beta)
Supports 1xH100 accelerator, see Hardware options for details.
- 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) - AI Runtime is now in Public Preview
Adds GPU support to serverless compute for deep learning workloads.
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- Declarative Feature Engineering APIs (Beta)
Define time-windowed aggregation features from data sources, materialize to Delta tables or Lakebase. Available in us-east-1 and us-west-2 regions.
- Endpoint telemetry for custom model serving endpoints (Beta)
Stores logs, traces, and metrics in Unity Catalog Delta tables using OpenTelemetry.
- 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.
- 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.
- 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.
- 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.
- Serverless compute has been updated to version 17.3
Updated from version 17.2, requires no configuration changes.
- 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.
- 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.
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.