Releasesby GlyphShare metric views with OpenSharing (Beta)
You can now share metric views with Databricks users in other metastores or accounts using OpenSharing. See Add metric views to a share and Read shared metric views .
Also shipped Sep 3, 2026Databricks in September 2026 →
Conversational analytics now supports questions about market basket analysis
Conversational analytics now supports questions about market basket analysis . This feature is generally available (GA).
External lineage (General availability)
External lineage is now generally available and is no longer in Preview .
Restricted Session Scope for agents (General availability)
With this release, Restricted Session Scope (RSS) is generally available. An RSS is a privilege ceiling that limits what an agent can do on behalf of a user. It intersects with RBAC and never grants privileges the user doesn't already have through their roles.
Gemini Enterprise: Latency and error rate views for agents
To monitor operational telemetry for your agents, use the two new views on the Observability tab: Latency: Shows response times for your agents. This view displays p50 (median) and p95 (95th percentile) metrics for Time to First Token (TTFT), Time to First Answer (TTFA), and Time to Last Token (TTLT).
Gemini Enterprise: General availability of Workflow Builder (formerly Agent Designer)
Workflow Builder (formerly known as Agent Designer) is generally available (GA) in Gemini Enterprise. Workflow Builder enables users across your organization to build multi-step automated workflows to streamline tasks and connect to enterprise data.
Lyria 3.5 generally available (GA)
Released the next generation of Google's music generation model: lyria-3.5: Full-length song generation with improved musical coherence, natural vocals, and fine-grained duration and structural control. The model supports text and image inputs and generates high-fidelity 44.1 kHz stereo audio. See the Music generation guide for details and code samples.
More from Databricks SQLEvery Databricks SQL release →
Databricks SQL version 2026.36 is now available in Preview
Databricks SQL version 2026.36 is now available in the Preview channel. See features in 2026.32 .
Databricks SQL version 2026.36 is rolling out in Current
Databricks SQL version 2026.36 is rolling out to the Current channel. See features in 2026.32 .
time_bucket SQL function aligns timestamps to fixed-width time buckets
time_bucket returns the start of the fixed-width interval a timestamp falls into, aligned to an origin you choose (for example, 15-minute or 3-month buckets). Use it instead of date_trunc when the bucket width or start is not a calendar unit. See time_bucket function .
Databricks SQL version 2026.32 is rolling out in Current
Databricks SQL version 2026.32 is rolling out to the Current channel. See features in 2026.32 .
Window measures on a numeric index column in metric views
Window measures support unitless offset and trailing / leading ranges on a consecutive integer order column. Use a numeric index for non-calendar periods such as fiscal weeks or 4-4-5 periods. See Window measures on a numeric index column .
Sharing metric views with OpenSharing is now generally available
Sharing metric views with OpenSharing is now generally available. Add metric views to a share and query them with MEASURE(...) on serverless compute. See Add metric views to a share and Read shared metric views .
Databricks SQL version 2026.32 is now available in Preview
Databricks SQL version 2026.32 is now available in the Preview channel. Review the following section to learn about new features and improvements. Validate VARIANT values with is_valid_variant The is_valid_variant function returns true when its input is a well-formed VARIANT value and false otherwise.
Alert system tables are in Public Preview
The system.alert schema is in Public Preview . This schema contains the alerts table, which records the configuration of every alert, and the alert_evaluation_history table, which records one row per alert evaluation. Use these tables to audit alert definitions, analyze evaluation trends, and monitor alert workloads at scale.