Databricks Rolls Out Automatic Change Data Feed for Delta Lake and Apache Iceberg
Databricks is rolling out Automatic Change Data Feed (Auto CDF) to workspaces, expected to be available in all supported regions by October 2026. This feature computes row-level changes at query time using row tracking, removing the need to enable CDF on individual Delta Lake or Apache Iceberg v3 tables. It streamlines data change capture for engineers working with large data lakes. Auto CDF requires Databricks Runtime 19 or above with row tracking enabled.
Features (1) ›
- Automated change data feed for Delta Lake and Apache Iceberg
Automatic change data feed (Auto CDF) is rolling out, simplifying how row-level changes are tracked in Delta Lake and Apache Iceberg v3 tables. It computes changes at query time via row tracking, eliminating the need for manual enablement per table. This feature requires Databricks Runtime 19+ with row tracking enabled.
https://docs.databricks.com/aws/en/release-notes/whats-coming#automatic-change-data-feed-will-soon-be-available-in-all-supported-regions
Related releases
- Automatic Change Data Feed is Generally Available on Databricks Databricks Release Notes ·
- Databricks Runtime 19 introduces Automatic Change Data Feed GA for Delta Lake Databricks Release Notes ·
- Databricks Delta Lake Sharing with Iceberg Reads Reaches GA Databricks Release Notes ·
- Databricks SQL adds MATCH_RECOGNIZE operator for sequence pattern detection Databricks Blog ·
- Databricks Lakeflow Jobs to Support JAR Tasks on Serverless Compute for Compliance Profiles Databricks Release Notes ·
- Databricks Apps Enabled by Default for Compliance Workspaces Databricks Release Notes ·