Databricks releases, every cloud
- JAR tasks on serverless compute will soon be available for workspaces with the compliance security profile enabled Coming soon
Replaces cluster provisioning, available in Lakeflow Jobs.
- 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.
- Standard performance mode is now available for one-time runs in the Jobs API
Sets performance_target to STANDARD. Supports Apache Airflow's DatabricksSubmitRunOperator.
- Maintenance windows for continuous pipelines
Sets daily 1-hour window for platform updates. Configured via Jobs UI, Pipelines UI, or Jobs REST API.
- Managed tables in Lakeflow pipelines (Beta)
Creates tables that Lakeflow manages, replacing manual table creation, and supports migrating existing Structured Streaming workloads.
- The Azure Databricks Excel Add-in is now generally available
Connects Excel to Azure Databricks workspace for querying and data import. Enables Live query for pivot tables.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- The Databricks Excel Add-in is now generally available
Connects Excel to Databricks workspace for querying and data import. Enables live query for pivot tables.
- Anaplan connector (Beta)
Ingests Anaplan audit trail events and user account records into Databricks.
- Anysphere Organization connector (Beta)
Ingests organization members and groups into Databricks via Anysphere Admin API. Requires API key authentication.
- Celigo connector (Beta)
Ingests Celigo audit log events into Databricks using an API token.
- Genie Code adds conversation controls
Lets you fork conversations, use /btw for side questions, and edit earlier messages.
- Incremental ingestion for Salesforce formula fields in Lakeflow Connect will soon be generally available Coming soon
Replaces full snapshot default, improving performance and reducing cost.
- Zerobus Ingest into default storage is now in Public Preview
Supports tables backed by default storage, requires Lakeflow Connect setup.
- Apache Arrow support for Zerobus Ingest is now generally available
Replaces JSON and Avro formats, requires Lakeflow Connect.
- Automatic change data feed is now generally available
Requires Databricks Runtime 19 or above with row tracking enabled. Makes MERGE and UPDATE operations about 15% faster.
- Databricks Runtime 19: September 1, 2026
Replaces manual change data feed enablement, requires row tracking enabled.
- Databricks Runtime maintenance updates (09/01)
Includes bug fixes, security patches, and performance improvements for versions 13.3 to 18.2.
- Genie Code scheduled tasks are now generally available
Runs prompts on a recurring schedule, producing a continuable Genie chat with results.
- Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
- Genie Code scheduled tasks will soon be available by default for workspaces with the compliance security profile enabled Coming soon
Replaces manual runs of recurring analysis tasks. Available in October 2026.
- Pipeline events system table is in Beta
Records Lakeflow pipeline event logs, capturing lifecycle transitions and errors, for querying and building alerts.
- Atlassian Audit Logs connector (Beta)
Ingests Atlassian organization audit log events using an API key.
- Genie Code for AI Runtime (Public Preview)
Generates distributed training code and resolves environment issues. Requires AI Runtime.
- Genie Code is now available as a Lakeflow Jobs task (Beta)
Runs prompts autonomously, reading upstream outputs and calling tools as needed, returning a conversation link.
- Zerobus Ingest into streaming tables is now generally available
Works like writing to a managed Delta table with same limits and quotas.
- Anysphere Audit Logs connector (Beta)
Uses Anysphere Admin API to ingest audit-log events, requires Cursor Admin API key.
- Connect to the Databricks Genie app in Microsoft Teams with your workspace URL (Public Preview)
Replaces server hostname with workspace URL for connection.
- Verkada connector (Beta)
Ingests Verkada organization audit logs and access users using a Verkada API key.
- 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.
- Performance mode now applies to materialized view and streaming table refreshes from dbt tasks
Now applies to dbt tasks, with optional Standard mode for lower costs, increasing latency to 4-6 minutes.
- Salesforce connector mTLS authentication is now generally available
Replaces OAuth client credentials flow for API-only users, requires client certificates.
- Choose an effort level in Genie Code
Sets balance between response quality and cost, defaults to Auto for highest quality.
- Genie Code supports file uploads
Uploads are used as chat context, see Attach files for details.
- Workiva connector (Beta)
Ingests Workiva audit activity, users, and roles using OAuth2 client credentials.
- Gmail connector in Lakeflow Connect (Beta)
Ingests messages, labels, drafts, filters, and profile data using a Google service account.
- SendGrid connector (Beta)
Ingests SendGrid subuser directory and IP access activity using a parent-account API key.
- SQL alert task in Lakeflow Jobs is now available by default for workspaces with the compliance security profile enabled
Supports all Databricks compliance security profile standards, returns evaluation state as output.
- Amplitude connector (Beta)
Ingests product analytics event data with metadata from Amplitude.
- Glean connector in Lakeflow Connect (Beta)
Ingests company-wide usage insights using a Glean Client API token.
- REPLACE USING flows for standalone streaming tables (Beta)
Replaces rows matching specified key columns, requires SEQUENCE BY column.
- Notion connector (Beta)
Ingests Notion pages, databases, and users into Databricks.
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.