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.
- Git Folder Serverless is in Beta
Shares serverless compute and pyproject.toml environment across notebooks and files.
- 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.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- 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.
- 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.
- 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) - 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.
- 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) - Workspace admin setting for serverless notebook execution timeout
Replaces manual override process, defaults to 2.5 hours.
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- Instance events and instance pools system tables are now available (Public Preview)
Track instance state transitions and instance pool configurations via system.compute.instance_events and system.compute.instance_pools tables.
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) - 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.
- 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) - 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) - Compute log delivery to volumes is now GA
Delivers Spark driver, worker, and event logs to Unity Catalog volumes, recommended for log storage.
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.
- Serverless compute is enabled by default
Eligible Google Cloud workspaces are affected, account admins no longer need to manually enable it.
- 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.
- Store and query MLflow traces in Unity Catalog (Beta)
Stores MLflow traces in Delta tables for long-term retention and analysis using OpenTelemetry format.
- 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.
- Flexible node types are now generally available
Falls back to alternative instance types when specified type is unavailable, improving launch reliability.
- 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.
Headlines, dates and product areas are Databricks' own, and every item links to the note it came from. The one-line summaries are ours.