📄 Document Intelligence REST APIs for parsing, extraction, and classification are now GA. Apps and agents can process documents as they arrive, extract structured data, and surface optional citations for review. Plus, ai_decide is in Beta for routing.

A great Genie demo is just the beginning. Here's how to turn early momentum into trusted, organization-wide adoption. → Start with one team and a clear set of business questions → Test answers against known-correct results → Refine business definitions based on feedback → Expand to adjacent teams as accuracy and governance checks are met Read the step-by-step guide:

You ship code in seconds and build apps, agents, and AI products faster than ever. So why does your database still take hours to provision? Lakebase is a new category of serverless Postgres database built for the way teams write software today, with instant branching, separate compute and storage, and architecture designed to scale with app and agent workloads. Read 𝘓𝘢𝘬𝘦𝘣𝘢𝘴𝘦 𝘍𝘰𝘳 𝘋𝘶𝘮𝘮𝘪𝘦𝘴 to learn: • Why traditional databases break down under modern app and agent workloads • How separating compute from storage changes cost, speed, and reliability • What instant branching and cloning unlock for development teams • How the lakebase architecture fits alongside your lakehouse for unified transactional and analytical work

You can write data back to Databricks without leaving Excel. Use the Databricks add-in for Excel to make changes and publish them to Unity Catalog tables, with write permissions enforced. Here's how it works ↓

Agents can build software. But what about the databases behind it? Databricks VP of Engineering and @neondatabase co-founder @nikitabase joined @MTSlive to talk about database branching, serverless architecture, and building for both AI agents and enterprise workloads.

Enterprise AI is only as useful as the data and business context behind it. At #DataAIWorldTour# 2026, see how organizations are building AI apps and agents grounded in their enterprise data, while maintaining control over usage, costs, and choice. Join Databricks leaders, customers and partners for the latest on Genie, Agent Bricks, Lakebase and Unity Gateway. 13 free, one-day events remain across North America, Europe and Asia. Find a stop near you:

Spatial SQL and spatial joins are now supported on Lakehouse//RT! In SpatialBench, queries ran up to 38X faster at 50 concurrent users than a traditional cloud data warehouse, among queries it could complete.

Introducing Apache Spark® 4.3, now available in Databricks Runtime 19! The release brings major new capabilities across real-time processing, history-preserving pipelines, small-data performance, Spark Connect, and SQL. What’s new: - Bring state to Real-Time Mode with streaming aggregation and transformWithState - Preserve history with SCD Type 2 Auto CDC - Iterate faster on small data with Project Feather - Reach Spark from more applications with expanded Spark Connect capabilities It also begins a new quarterly feature-release cadence, bringing completed improvements to users sooner. Get started:

Multi-statement transactions are now GA on Databricks, supporting Delta Lake and Apache Iceberg! Run multi-step warehouse workflows atomically, directly on the lakehouse, without needing a separate warehouse.

Kimi K3.1 Pro is available on Databricks on day 0. Build governed AI apps and agents on Lakehouse data with Kimi K3.1 Pro and 70+ other models. Unity Gateway lets you govern, monitor and secure calls, and test models without changing app code.

We benchmarked Lakebase Search on 1M to 4M passages to understand how vector search performs as the index grows. Here's what we learned 👇 Cache size relative to the vector index mattered more than row count. When the cache roughly matched the index, 95–98% of page reads avoided storage and warm vector search p50 latency stayed between 11 and 23 ms. As datasets grow, sizing the cache alongside the vector index helps maintain low-latency search.

Your Iceberg tables shouldn't be locked into a single catalog. REGISTER and UNREGISTER enable transfers between catalogs without copying data, while reducing split-brain risk. More on the open standard:

Join Databricks Co-founder and CEO @alighodsi and @OpenAI co-founder and President @gdb, and other special guests at DATA + AI LIVE to hear exciting announcements about the next generation of Genie, the data smart AI coworker. Get a first look on Nov 11 at 9 AM PT. Save your spot:

Stripe Data Pipeline now supports real-time sync to Lakebase Postgres! With updates arriving within seconds, apps can use SQL to manage feature access, display billing details, and deliver personalized offers.

AI research is changing as agents take on more of the experimentation loop. Instead of manually running every trial, our researchers increasingly use agents to propose changes, launch parallel experiments, evaluate results, and decide what to try next. Across our AI Functions research workloads, training jobs have grown 8x. At that scale, launch latency and GPU reliability become critical. Here's how we're using AI Runtime to keep up with the pace of agent-driven research.

More ways to build, validate, and manage data preparation workflows in Lakeflow Designer 🫡 Our October roundup highlights the latest enhancements: • Guardrails for data quality checks, with control over what happens when checks fail • No-code operators for cleaning and deduplication • Multi-table joins in a single operator • Parameterized inputs and outputs • Visual version history to easily review workflow changes

[DEMO] Your AI agents can query data. But do they understand what it means? See how Genie Ontology, Genie One, MCP, and Unity Gateway help agents use trusted business context with guardrails in place. Watch the demo:

We're excited to expand our partnership with @SAP this week at #SAPTechEd#! AI needs business context, and much of it lives in SAP systems. The new SAP Application Data Foundation simplifies access to cloud and on-premises application data in SAP Databricks, helping reduce custom pipelines, TCO, and time to value. With Genie, Lakebase, Unity Gateway, and Lakeflow coming to the platform, teams can put that data to work across analytics, apps, and AI agents.