When implementing Slowly Changing Dimensions (SCD) in a Databricks Lakehouse, what is the fundamental difference between the Type 1 and Type 3 approaches?

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Last updated: January 6, 2026 at 15:40

Type 1 maintains a full version history of all changes, whereas Type 3 utilizes external snapshots for auditing.

Type 1 overwrites existing records without preserving history, whereas Type 3 stores a limited history by adding specific columns (such as previous_value) to the record._

Type 1 preserves historical data through versioning, while Type 3 overwrites current records with new values.

Type 1 archives changes in a separate audit table, while Type 3 avoids any archival of historical data.

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When implementing Slowly Changing Dimensions (SCD) in a Databricks Lakehouse, what is the fundamental difference between the Type 1 and Type 3 approaches?