Delta Lake’s Change Data Feed (CDF) is a key feature for building incremental pipelines. When enabled on a Delta table, CDF tracks row-level changes between versions of that table. In practice, this means your pipelines can process only the rows that changed since the last run, instead of scanning entire tables. For example, rather than comparing two multi-terabyte snapshots, you can quickly retrieve just the handful of rows that were updated. This greatly simplifies ETL/ELT workloads by avoiding full-table scans.
Enabling Change Data Feed
Before you can read changes, CDF must be enabled on the table. In Databricks, you set the table property delta.enableChangeDataFeed = true when creating or altering a Delta table. For instance, in PySpark, you might run: