Data and AI releases

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Lakebase backup schedule API (Beta)

BetaVerified

You can now manage Lakebase backup schedules programmatically. The snapshot schedule API lets you read and set a root branch's automated snapshot cadences (daily, weekly, or monthly) and how long each cadence's snapshots are retained. This API is in Beta and available to all Lakebase workspaces. See Create a backup schedule .

Developer tools

Read on docs.databricks.com

Also shipped Sep 22, 2026Databricks in September 2026 →

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Lakebase observability telemetry in system tables (Beta)

Lakebase captures its Postgres observability telemetry into the system.lakebase system tables, with no configuration to create and no destination to choose. Query plans, session history, wait events, schema-change history, database and compute health, and Postgres logs land there, and records are retained for 7 days.

Beta
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ai_search can search Lakebase synced tables (Beta)

The ai_search function can now retrieve from Lakebase synced tables with Lakebase Search enabled, in addition to AI Search indexes. Add a lakebase_search knowledge source to search a Lakebase synced table, or combine it with vector_search sources in the same call. This feature is in Beta . See ai_search function .

Beta
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Lakebase Search is generally available

Lakebase Search is now generally available. It brings scalable vector and keyword search to Lakebase projects through two Postgres extensions, so you can run semantic and exact-term search in a single database without a separate search stack: lakebase_vector adds the lakebase_ann index type for approximate nearest-neighbor vector search.

GA
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Lakebase snapshots API (Beta)

You can now manage Lakebase snapshots programmatically. The snapshots API lets you create, get, list, and delete point-in-time snapshots of a project branch, and restore a snapshot by creating a new branch from it. This API is in Beta. See Create a snapshot .

Beta
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LTAP Direct Writes is generally available

LTAP Direct Writes is now generally available. It speeds up how synced tables load into Lakebase by writing the initial load and full refreshes directly to the storage layer instead of through your compute endpoint, so large loads finish faster without competing with your queries.

GA
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