Databricks releases, every cloud
- Serverless compute now available for compliance standards
Adds HITRUST, PCI-DSS, TISAX, and UK Cyber Essentials Plus support.
- Google Ads connector (Beta)
Ingests data from Google Ads into Databricks via Lakeflow Connect.
- New GCP regions support serverless compute
Available in me-central1 and southamerica-east1 regions.
- Zendesk Support connector (Beta)
Ingests ticket, help center, and community forum data from Zendesk Support.
- Trigger on update for pipelines (GA)
Refreshes pipeline when source table changes, usable in Databricks SQL pipeline schedules.
- View and restore your recent workspace tab sessions
Restores up to 10 recent sessions.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Google Drive connector (Beta)
Supports read_files, spark.read, COPY INTO, and Auto Loader for ingesting files.
- 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.
- Ingest Salesforce formula fields incrementally (Beta)
Replaces snapshotting with incremental ingestion, improving performance and reducing costs.
- Row filtering for managed ingestion connectors (Beta)
Applies conditions like a SQL WHERE clause, available for Google Analytics, Salesforce, and ServiceNow connectors.
- Meta Ads connector (Beta)
Ingests data from Meta Ads, requires setup as a data source.
- Serverless compute is now available in Azure China North 3
Available for notebooks, jobs, pipelines, and SQL warehouses.
- Confluence connector (Beta)
Ingests Confluence spaces and pages into Databricks, requires OAuth U2M configuration.
- Serverless workspaces are now available in new GCP regions
Available in most GCP regions, see documentation for list.
- Change owner for materialized views or streaming tables defined in Databricks SQL
Done through Catalog Explorer, replacing previous methods.
- Customizable SharePoint connector (Beta)
Ingests structured, semi-structured, and unstructured files into Delta tables with customizable schema inference and parsing options.
- Discover files in Auto Loader efficiently using file events
Requires file events enabled on external locations. Replaces directory listing for efficiency.
- Jira connector (Beta)
Ingests Jira issues, comments, and attachments metadata into Databricks.
- Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
- Configure full refresh behavior for managed database connectors
Applies to Lakeflow Connect managed database connectors, allowing scheduled full refresh snapshots and automatic recovery from unsupported schema changes.
- Serverless compute is now available in new regions
Added to Australia Southeast, Canada Central, Mexico Central, Norway East, and South Africa North regions.
- Jobs can now be triggered on source view update
Supports views referencing supported table types, see documentation for specifics.
- Improved full refresh flow for managed database connectors
Reduces downtime by delaying table refresh until snapshot completion, minimizing PENDING_RESET errors.
- Lakeflow Declarative Pipelines has been renamed to Lakeflow Spark Declarative Pipelines
Replaces Lakeflow Declarative Pipelines, see Spark Declarative Pipelines for details.
- Serverless notebook tasks can now use jobs environment
Replaces inherited serverless environment with configurable job environment.
- JAR tasks are now supported on serverless compute
Run JAR jobs without a cluster.
- Salesforce ingestion connector supports history tracking (SCD type 2)
Enables history tracking, overwriting default SCD type 1 behavior.
- Serverless compute has been updated to version 17.3
Updated from version 17.2, requires no configuration changes.
- Jobs can now be triggered on source table update
Triggers require Databricks Runtime 7.0 or later.
- Create backfill job runs
Triggers job runs to load past data, useful for repairing processing failures.
- 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.
- New requirement to create connections for Salesforce ingestion
Requires Databricks connected app installed. Applies to new connections only.
- Google Analytics Raw Data connector GA
Enables ingestion of raw Google Analytics data into Databricks, requires Google Analytics 4 and Google BigQuery setup.
- Python custom data sources can be used with Spark Declarative Pipelines on Lakeflow
Supports Python custom data sources and sinks in pipeline definitions.
- SQL Server connector supports SCD type 2
Maintains a history of changes, rather than overwriting outdated records.
- Microsoft SQL Server connector GA
Replaces manual ingestion scripts, requires Lakeflow Connect setup.
- Set the run-as user for Spark Declarative Pipelines on Lakeflow
Replaces user accounts with a service principal for automated workloads.
- Jobs in continuous mode can now have task-level retries for failed tasks
Task-level retries replace job-level retries, require continuous mode.
- ServiceNow connector GA
Replaces manual API configuration, requires Lakeflow Connect setup.
- Jobs & Pipelines list now includes Databricks SQL pipelines
Includes materialized views and streaming tables created with Databricks SQL.
- Parent tasks (Run job and For each) now have a separate limit
Separate limit doesn't count against overall limit, see Resource limits.
Headlines, dates and product areas are Databricks' own, and every item links to the note it came from. The one-line summaries are ours.