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databricks Platform · Updated Nov 21, 2025

Configure full refresh behavior for managed database connectors

You can now schedule when full refresh snapshots occur and enable automatic full refresh to recover from unsupported schema changes.

Update Open docs ↗release note ↗
What it does

You can now schedule when full refresh snapshots occur and enable automatic full refresh to recover from unsupported schema changes. This applies to managed database connectors like SQL Server in Lakeflow Connect. Applies to: SaaS connectors Database connectors Query based connectors Fully refreshing the ingestion pipeline clears the data and state of the target tables, then reprocesses all records from the data source.

Why it matters

Full refresh behavior (CDC) Applies to: SaaS connectors Database connectors When you trigger a full refresh of a table, Databricks optimizes the process to reduce downtime and maintain data availability: 1.

Key capabilities
table: sourceschema: sourcetable:
table: sourceschema: sourcetable: destinationcatalog: destinationschema…
MONDAY
MONDAY
TUESDAY timezoneid: 'America/LosAngeles'
TUESDAY timezoneid: 'America/LosAngeles'
table: sourceschema: sourcetable:
table: sourceschema: sourcetable: destinationcatalog: destinationschema…
Architecture
Databricks Platform → Platform
In short

You can now schedule when full refresh snapshots occur and enable automatic full refresh to recover from unsupported schema changes. This applies to managed database connectors like SQL Server in Lakeflow Connect.

Read the full documentation ↗
Key takeaway
You can now schedule when full refresh snapshots occur and enable automatic full refresh to recover from unsupported schema changes.
2025-11-21-configure-full-refresh-behavior-for-managed-database-connectors Generated by the Databricks Updates Agent · browse all updates