Databricks

Today we're announcing Genie Code, your autonomous AI partner for data. Genie Code is a state-of-the-art agent that lets data teams move from prompting a copilot to delegating real work: building pipelines, machine learning models, debugging failures, and shipping dashboards. This isn't a smarter autocomplete. It's a different kind of AI partner entirely. Unlike general coding agents that stop once the code is built, Genie Code plans, executes, and iterates across the full data and AI lifecycle inside Databricks. It's purpose-built for data engineering, data science, and BI: • More than doubles the success rate of leading coding agents on real-world data science tasks • Proactively monitors your pipelines and AI models in the background, triaging failures and fixing issues before a human intervenes • Works with your data wherever it lives, across Databricks and external platforms, with full governance and MCP support This is what the future of data work looks like. databricks.com/blog/introduci…

Great evening at @daytonaio AI Builders in @databricks NYC Office🗽 Packed room, insightful talks, and practical insights on AI Engineering from @JukicVedran, @markospetko, @pauljaffre & @GeoffreyHuntley. Big thanks to @databricks & @sentry, and everyone who joined!🚀

Today at #NVIDIAGTC, we’re introducing AI Runtime, with serverless NVIDIA A10 and H100 GPUs now available on Databricks for training and fine-tuning. GPU infrastructure has been one of the biggest blockers for teams building advanced AI, from long procurement cycles to complex distributed setups and data bottlenecks. AI Runtime removes that friction: - On-demand GPUs with no cluster management - Optimized distributed training with key frameworks pre-installed - Native integration with Lakeflow, MLflow, and Unity Catalog With AI Runtime, teams can focus on building and shipping models, not managing infrastructure. databricks.com/blog/introduci…

Real-Time Mode for Apache Spark Structured Streaming on Databricks is now generally available. For ultra-low latency workloads, teams have historically needed to run separate, specialized engines like Apache Flink alongside Spark, duplicating codebases, governance, and operational overhead. RTM eliminates that by bringing millisecond-level latency to the Spark APIs you already use. Industry-leading companies are already seeing results: - @coinbase cut end-to-end latency by 80%+ while computing 250+ ML features on a unified Spark engine - @DraftKings rebuilt fraud detection pipelines for live sports betting with latencies that weren't previously possible - @makemytrip hit sub-50ms P50 latencies and saw a 7% lift in click-through rates If you're already on Structured Streaming, a single config update is all it takes to get started. databricks.com/blog/announcin…

GPT-5.4 Mini and GPT-5.4 Nano are available on Databricks today. Both models run on your enterprise data with the governance and operational tooling teams need for production. GPT-5.4 Mini brings meaningful gains over GPT-5 Mini in coding, reasoning, multimodal understanding, and tool use, at more than 2x the speed. GPT-5.4 Nano is the smallest and most cost-efficient option in the GPT-5.4 family, built for classification, data extraction, ranking, and simpler coding subagents. Congrats to the @OpenAI team. Looking forward to seeing what our customers build! #openai-gpt-54-mini-and-gpt-54-nano-now-available-as-databricks-hosted-models" target="_blank" rel="nofollow noopener">docs.databricks.com/aws/en/release…

At FabCon 2026, Azure Databricks is introducing new capabilities across Lakebase, Lakeflow, and Genie to make it easier to build data and AI applications on Azure. What’s new: • Azure Databricks Lakebase is now GA as the operational database for AI agents • Lakeflow Connect Free Tier allows you to ingest ~100 million records/workspace/day from many popular enterprise data sources • Databricks One Mobile enables access to AI/BI, dashboards, and Genie on-the-go • Genie and Genie Code expand AI-powered analytics and enable agentic workflows for data teams • Azure Databricks Excel add-in connects Excel directly to governed lakehouse data Together, these capabilities simplify how data is ingested, governed, and used to power analytics and AI on Azure. databricks.com/blog/whats-new…

The next wave of data and AI innovation will be on full display at Data + AI Summit 2026. See how teams are using Lakebase, serverless Postgres for apps and AI agents, and Genie, a conversational AI agent for data insights — plus keynotes, live demos, and sessions from the builders shaping the future. Join us June 15-18: databricks.com/dataaisummit?u…

Serverless Workspaces in Azure Databricks are now generally available! Teams can now spin up fully managed workspaces in minutes — no VNet design, compute provisioning, or infrastructure setup required. With serverless compute, Databricks-managed storage, and governance through Unity Catalog built in, @Azure data and AI teams can quickly move from platform setup to delivering analytics, BI, and AI. databricks.com/blog/serverles…

"You can think of this as RAG — but like RAG plus plus plus plus plus plus, all the way up to 200 vector database calls." — @jefrankle, Chief AI Scientist at Databricks. We published new research on KARL — Knowledge Agents via Reinforcement Learning — a RAG agent trained simultaneously across six distinct enterprise search behaviors. Most pipelines are built for one and fail silently on the others. KARL generalizes across the kinds of ambiguous, fragmented, real-world queries that enterprise search actually demands. Read more via @VentureBeat: venturebeat.com/data/databrick…

Databricks CEO and co-founder @alighodsi is taking the stage at #RSAC2026 to address the most critical challenge in security: the shift from manual operations to machine-scale AI automation. Hear why today's security stack — built for yesterday's data volumes and human-speed threats — is no longer enough. Ali will break down what's coming next and why an open, agent-first architecture is the path forward for CISOs. path.rsaconference.com/flow/rsac/us26…

Delta Sharing now supports Attribute-Based Access Control. Providers can now share these tables directly without creating separate copies, and recipients can apply their own ABAC policies with the guarantee of correct query-time enforcement. Every read, every policy creation, and every share event is logged in Unity Catalog for auditing and compliance. Secure data sharing at scale should not require choosing between control and convenience. databricks.com/blog/how-delta…

Agentic analytics is changing how data teams work, and it's happening faster than expected. Ken Wong from Databricks, @rgb_prithvi from @AnthropicAI, and other experts discuss how agents built on a unified data platform can support every step of your analytics workflow. Explore: - The latest innovations in Lakeflow Designer, Unity Catalog Business Semantics, AI/BI Genie, and more - How Genie and Claude deliver agentic data insights - How to build your first agentic analytics workflow for free and never pay for BI seats again databricks.com/resources/webi…

Most critical enterprise data doesn't live in organized column and rows. It's unstructured – PDFs, reports, and diagrams. Extracting insights historically meant rules-heavy OCR pipelines that break the changes. @Alex_TheAnalyst walks through how document processing in Databricks replaces all of that with AI-powered extraction that's flexible, accurate, and easy to maintain. Watch the full walkthrough: youtu.be/ItzSyfNEptk?si…

Push 10+ GB/sec to your lakehouse in under 5 seconds. With Zerobus Ingest, stream data directly into your lakehouse — no message bus required. Less infrastructure to manage, lower costs, and faster access to real-time data. Key capabilities: • Sub-5-second latency for thousands of concurrent connections • Supports over 10 GB/sec aggregate throughput to a single table • Includes gRPC and REST APIs, plus SDKs for Python, Java, Rust, Go, and Typescript • Built-in governance with Unity Catalog Now generally available: databricks.com/blog/announcin…

In data and AI, validated expertise is becoming a real differentiator — for career growth, credibility, and visibility. Professionals with Databricks certifications report tangible outcomes: promotions, expanded opportunities, stronger credibility in leadership discussions, and increased engagement and reach on professional networks. The certification has become a practical lever for moving into higher-responsibility roles and making an impact at scale. Ready to take the next step? Explore Databricks certifications: databricks.com/blog/professio…

One in four Y Combinator startups is already shipping with 95% AI-generated code. Building at that speed is now possible without creating data silos or stepping outside your existing security controls. This tutorial walks through how to build a full-stack app inside Databricks using Lakebase for managed Postgres, Databricks Apps as the secure runtime, and AI assistance in your IDE, including a four-step context engineering workflow to make AI coding reliable and consistent. youtu.be/ninPbwHnqkw?si…

Turn enterprise documents into answers your teams can trust. With Agent Bricks Knowledge Assistant, teams can: - Launch a managed knowledge agent in minutes - Get accurate, page-level citations - Improve answer quality with Instructed Retrieval - Apply expert guidance at scale with ALHF Explore how it works → databricks.com/blog/agent-bri…

Data questions don't happen in a vacuum. They come up mid-conversation in Microsoft Teams, in a Slack thread, or inside a custom app. But getting a governed, accurate answer has always meant switching contexts or waiting on someone else. Databricks Genie now works directly inside the tools your teams already use, including Microsoft Teams, Slack, Confluence, and custom web apps. With enterprise OAuth, every conversation is authenticated and governed by each user's own data permissions, so the right people see the right data, wherever they're asking. databricks.com/blog/access-ge…

What are the defining traits of companies that put their AI initiatives into production? We looked at actual usage data across 20,000+ customers worldwide to identify the building blocks to a successful enterprise AI strategy. One key finding: AI evaluation tools have become a powerful lever for producing high-quality outputs required for AI in production. Companies using evaluations tools get nearly 6x more AI projects into production than that don’t. Get more insights in the 2026 State of AI Agents: databricks.com/resources/eboo…

For years, data teams have maintained two separate systems: - A warehouse for multi-step SQL workflows - A Lakehouse for analytics and AI That split means duplicate pipelines, higher TCO, and operational complexity. Today that changes. Databricks now supports multi-statement, multi-table transactions across Delta and Iceberg, with row-level concurrency and no locks. Combined with Stored Procedures and SQL Scripting, customers can confidently migrate mission-critical warehousing workloads to the lakehouse. Warehousing, analytics, and AI on one architecture. databricks.com/blog/transacti…

Data + AI Summit is where data, dev and AI teams go to level up. Whether you're building AI agents, scaling real-time pipelines, or trying to get more projects out of pilot and into production, the 2026 agenda is built for the practitioners doing the actual work. 800+ hands-on sessions and deep technical dives across: - App Development - AI/ML & Agents - Analytics & BI - Data Engineering & Streaming - Data Sharing & Collaboration - Data Warehousing - Governance & Security Register today to take advantage of early-bird pricing: databricks.com/dataaisummit?u…