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databricks Platform · Updated Sep 1, 2026

Automatic change data feed is now generally available

Automatic change data feed (Auto CDF) computes row level changes at query time using row tracking, without requiring you to manually enable change data feed on each Delta Lake or Apache Iceberg v3…

What it does

Automatic change data feed (Auto CDF) computes row level changes at query time using row tracking, without requiring you to manually enable change data feed on each Delta Lake or Apache Iceberg v3 table. Auto CDF removes write time overhead and makes MERGE and UPDATE operations about 15% faster on tables that you query for changes. It works with batch queries, Structured Streaming, and Delta Lake Sharing, and requires Databricks Runtime 19 LTS or above with row tracking enabled.

Why it matters

Auto CDF removes write time overhead and makes MERGE and UPDATE operations about 15% faster on tables that you query for changes.

Key capabilities
A managed table in Delta
A managed table in Delta Lake format with row tracking enabled or in Iceberg v3 format.
An external table in Delta
An external table in Delta Lake format with row tracking enabled.
Architecture
Databricks Platform → Platform
In short

Automatic change data feed (Auto CDF) computes row level changes at query time using row tracking, without requiring you to manually enable change data feed on each Delta Lake or Apache Iceberg v3 table. Auto CDF removes write time overhead and makes MERGE…

Read the full documentation ↗
Key takeaway
Automatic change data feed (Auto CDF) computes row level changes at query time using row tracking, without requiring you to manually enable change data feed on each Delta Lake or Apache Iceberg v3…
2026-09-01-automatic-change-data-feed-is-now-generally-available Generated by the Databricks Updates Agent · browse all updates