Databricks Lakeflow Pipelines Now Support Managed Tables (Beta)
Databricks has introduced support for managed tables within Lakeflow pipelines, enabling users to create and write to them using append flows. This feature, currently in Beta, simplifies data management for pipeline users and enhances data consistency. It also facilitates migrating existing Structured Streaming workloads into Lakeflow pipelines without reprocessing source data. This update primarily affects engineers and architects building and managing data pipelines on Databricks.
- →Managed Tables Support in Lakeflow Pipelines
- →Migrate Structured Streaming Workloads to Lakeflow
Features (2) ›
- Managed Tables Support in Lakeflow Pipelines
Databricks Lakeflow pipelines now support creating managed tables and writing to them using one or more append flows. This capability, currently in Beta, streamlines data handling directly within pipeline definitions.
- Migrate Structured Streaming Workloads to Lakeflow
An `import_checkpoint` function has been added to append flows, allowing users to migrate existing Structured Streaming workloads into Lakeflow pipelines without reprocessing the source data.
https://docs.databricks.com/aws/en/release-notes/product/2026/september#managed-tables-in-lakeflow-pipelines-beta
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