Databricks releases, every cloud
- Data Classification now scans Unity Catalog views (Beta)
Scans Unity Catalog views in addition to tables, using the same detection engine, and is currently in Beta.
- 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.
- Organize your work with spaces
Preserves open tabs for specific folders or projects.
- Create a least-privilege Databricks workspace
Grants Databricks a narrow set of custom IAM roles instead of broad permissions on Google 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) - Data Classification is now available by default for additional compliance standards
Requires compliance security profile with C5, TISAX, or IRAP controls.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Data Classification is now available by default for some workspaces with the compliance security profile enabled
Requires compliance security profile and specific controls like HIPAA or HITRUST.
- 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) - 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) - 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) - Databricks Data Classification is now GA
Automatically classifies and tags sensitive data in Unity Catalog using AI.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Upcoming breaking change: default behavior when deleting a Unity Catalog pipeline Coming soon
Deletes now retain associated tables by default, set cascade=true to remove them.
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.
- Change to use_case field in VPC endpoint API responses Coming soon
Changes from WORKSPACE_ACCESS to GENERAL_ACCESS, see API docs for details.
- 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.
- Store and query MLflow traces in Unity Catalog (Beta)
Stores MLflow traces in Delta tables for long-term retention and analysis using OpenTelemetry format.
- Data Classification (Public Preview)
Supports all catalog types, consolidates results into a system table.
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- Data classification system table Beta
Captures sensitive data detections at column level across enabled catalogs.
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