Stop Hand-Coding Change Data Capture Pipelines

This post introduces AutoCDC in Lakeflow Spark Declarative Pipelines as a declarative alternative to hand-coded Change Data Capture and Slowly Changing Dimension pipelines.

• •SCD Type 1 and Type 2 pipelines are commonly hand-rolled with complex MERGE logic, window functions, and staging tables that grow fragile over time
• •AutoCDC replaces 40–200+ lines of custom pipeline logic with ~6–10 lines of declarative pipeline definition
• •Snapshot-based CDC is supported as a first-class pattern, automatically detecting row-level changes between snapshots without custom diff logic
• •The platform automatically handles out-of-sequence records, deduplication, idempotent reprocessing, and schema evolution
• •Recent Databricks Runtime improvements delivered ~71% net price-performance gain for SCD Type 1 and ~96% for SCD Type 2 since November 2025