Databricks releases, every cloud
- 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.
- Apache Arrow support for Zerobus Ingest is now generally available
Replaces JSON and Avro formats, requires Lakeflow Connect.
- Zerobus Ingest into streaming tables is now generally available
Works like writing to a managed Delta table with same limits and quotas.
- Salesforce connector mTLS authentication is now generally available
Replaces OAuth client credentials flow for API-only users, requires client certificates.
- 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.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- REPLACE WHERE flows are now generally available
Replaces full table reprocessing with row-level updates based on a predicate.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Lakeflow Connect row filtering is now generally available
Works like a SQL WHERE clause, applies to initial and incremental updates.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - SQL alert task in Lakeflow Jobs is now generally available
Evaluates a Databricks SQL alert as part of a Lakeflow Job, returning its state for downstream tasks.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - AUTO CDC flows for streaming tables in Databricks SQL are generally available
Automatically handles out-of-order records as SCD type 1 or 2, replacing complex MERGE INTO logic.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - The update_flow API for Spark Declarative Pipelines on Lakeflow is generally available
Writes to a sink in update output mode, emitting only changed rows. Supports stateful aggregations without a watermark.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Query-based connectors for Lakeflow Connect are now generally available
Ingests data from databases like Oracle and PostgreSQL without CDC configuration.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Refresh policies and EXPLAIN CREATE MATERIALIZED VIEW for materialized views are now generally available
Requires Databricks Runtime 17.3 and above. Available in Databricks SQL.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Unified runs list is generally available
Replaces separate job and pipeline run lists, adds filtering and error code visualization.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Spark Declarative Pipelines on Lakeflow sinks are now generally available
Supports writing to Delta tables, Kafka topics, and Azure Event Hubs.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks SQL alerts are now generally available
Monitors data and KPIs by running scheduled queries, notifying recipients when conditions are met.
- Lakeflow Pipelines Editor is now generally available
Offers agent-first experience with Genie Code for creating production pipelines.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Disabling tasks in Lakeflow Jobs is now GA
Disabled tasks retain config and run history, can be re-enabled later.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
- 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) - COMMENT ON streaming tables is now GA
Adds comments to streaming tables, previously only available for non-streaming tables.
- Applying filters, masks, tags, and comments to pipeline-created datasets is now GA
Modifies ETL and ingestion pipelines using CREATE, ALTER, or Lakeflow UI. Applies to Spark Declarative Pipelines on Lakeflow and Lakeflow Connect.
- Updated Lakeflow Jobs UI is generally available
Simplifies job creation and editing, see Lakeflow Jobs for details.
- Flexible node types are now generally available
Falls back to alternative instance types when specified type is unavailable, improving launch reliability.
- Spark Declarative Pipelines on Lakeflow stream progress metrics are generally available
Supports querying event log for stream progress metrics.
- Migrate Spark Declarative Pipelines on Lakeflow pipelines from legacy publishing mode is generally available
Replaces legacy mode that only published to a single catalog and schema. Now supports multiple catalogs and schemas.
- Migrate Spark Declarative Pipelines on Lakeflow from legacy publishing mode is now GA
Replaces legacy single-catalog publishing with multi-catalog support.
- New SQL editor is generally available
Provides a unified authoring environment with features like real-time collaboration and enhanced Databricks Assistant integration.
- Moving tables between Spark Declarative Pipelines on Lakeflow pipelines is now GA
Supports moving tables in Unity Catalog ETL pipelines.
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.