The agentic era is here. Hundreds of thousands of agents are now acting on enterprise data, querying it, reasoning over it, and making decisions with it in real time. That shift has changed what we ask of the catalog. The catalog has moved from a system of record to a runtime decision-maker for AI.
Making those decisions takes three things: control, so every action, human or agent, stays governed; context, so agents understand the business and stop hallucinating; and choice, so you're never locked into a single cloud, model, or format. Together, these are what governance has to mean in the agentic era.
Five years ago, Databricks pioneered data and AI governance by releasing Unity Catalog, the industry's only unified governance solution for data and AI across clouds, data formats, and data platforms. More than 14,000 organizations now govern their data and AI on Unity Catalog.
Today, we're advancing Unity Catalog to deliver on all three: control, context, and choice. Here's what's new.
For years, governing an asset meant governing access: who can query this table, who can call this model. But agents don't just access assets; they act through them, calling models, invoking tools, and connecting to MCP servers. To meet this shift, we are introducing a suite of capabilities built to govern the entire lifecycle of an agent's behavior.
Unity AI Gateway is our governance solution for enterprise AI. Built on Unity Catalog, it extends governance beyond data and AI assets to the runtime interactions between models, agents, MCPs, skills, and tools:
Read the full AI governance announcement.
Governance Hub, now in PrPr, provides a centralized command center for data stewards and admins to govern your Databricks estate: monitor your posture, identify risks, prioritize remediation, and scale governance operations across data, AI, cost, and performance from a single experience.
Recently, we announced the General Availability of ABAC policies for row filtering and column masking, alongside Governed Tags and Data Classification, to help you protect sensitive data at scale.
At Data + AI Summit, we are extending ABAC with:
Role-based access control (Public Preview coming soon) complements Databricks’ collaborative, inheritance-based identity and permission model by enabling customers to define groups that behave like roles. A role is just a group with a collection of permissions that users can assume. When a user assumes a role, they act as the role, and all actions, including data access are authorized as that role.
RBAC lets customers model new use cases, such as exclusive access, where roles provide data-isolation boundaries for projects that work with sensitive data where data sets should not be accessed in combination, e.g. clinical trials, or country-specific data, or when performing highly-privileged tasks, such as debugging access control issues. Users can easily switch between roles in the UI, or by specifying a role in client OAuth flows, and the workspace adapts to exactly what that role allows.
Agents are only as good as the context they have. Without a shared definition of what the business actually means, even a capable agent will guess. Unity Catalog Semantics provides agents and humans with a single, shared source of meaning. Concepts and business KPIs are defined once, organized by domain, and accessible via SQL, APIs, and MCPs, so any tool or agent can use them without lock-in. Now we're extending Unity Catalog Semantics with new capabilities to define and organize context.
Glossary lets you define authoritative concepts, terms, and taxonomies that help agents and people understand your business, or import the ones you already have. Glossary pages connect to the underlying data and to each other, capturing relationships. Genie Code drafts new Glossary pages, suggests refinements, and flags definitions that drift from how your data is actually used, while your whole team curates them together through suggestions, comments, and domain-level ownership. Preview of Glossary is coming soon.
Domains, now in Public Preview, organize your data and AI assets into business-aligned categories, giving agents scoped, relevant context instead of the entire catalog. Humans browse and agents query domains through an internal marketplace, with certification and stewardship signals showing what's reliable. AI-driven domain suggestions, coming soon in preview, propose domains for you automatically, so you don't have to organize everything from scratch.
This user-defined semantic foundation in Unity Catalog feeds the Genie Ontology, a continuously learned enterprise context layer in the Databricks Platform. Learn more about Genie Ontology in this announcement blog.
Metrics in Unity Catalog let you define your business KPIs like revenue, churn, active users, margin, once as governed, reusable objects, then query them consistently from SQL, BI tools, APIs, and agents. We're significantly expanding what you can model and how you author it:
Metrics is also open: it's open source, available in Apache Spark and Unity Catalog OSS, and its Open Semantic Interchange (OSI) ready.
External lineage, now generally available, extends Lineage in Unity Catalog to assets beyond Databricks. You can register upstream source systems and downstream BI reports so a single lineage graph spans your full data flow end-to-end. As part of this release, Lakeflow Connect managed ingestion pipelines automatically record lineage from source tables to their destination tables in Unity Catalog. This gives agents a fuller picture of where your data comes from and how it moves, so they can reason about it more reliably.
Table Insights in Unity Catalog now include a new derived signal: Column-level Popularity. From a table's overview page in Catalog Explorer, you can see the relative popularity of each column, measured by how many historical queries against the table read from it. This signal also feeds the Genie Ontology, giving it a sharper sense of which columns matter most when reasoning over your tables.
In the agentic era, you can't afford to be locked in. Compute is scarce, models change fast, and your data spans multiple clouds, regions, and formats. Your infrastructure has to flex across all of it, so you can run wherever capacity exists, keep data in the right region, work across formats, and adopt new models as they arrive, all without re-platforming. We are announcing several new capabilities to make that real.
Unity Catalog now extends governance across a customer's entire Databricks footprint, spanning accounts, regions, and clouds. A new four-level namespace (metastore.catalog.schema.table) gives every asset a single address across the entire estate, so you get a unified discovery experience, one set of access policies enforced consistently, one audit trail, and column-level lineage end to end. You can bring your Databricks workloads to whichever cloud and region has the right capacity, GPUs, or proximity to your data, and governance stays consistent everywhere those workloads run.
Managed Disaster Recovery, providing customers with resilience for their mission-critical workloads. It enables you to replicate the critical parts of your Databricks deployment to a secondary region and fail over to it within minutes of a disaster. Managed Disaster Recovery requires the new Mission Critical add-on, which unlocks both Managed Disaster Recovery and our existing Enhanced Security and Compliance capabilities.
Unity Catalog is the most comprehensive and open catalog across the Delta Lake and Apache Iceberg ecosystems, with recent advancements including Iceberg v3 GA, Managed Iceberg GA, new federation connectors, and cross-engine ABAC. At Data + AI Summit, we're going further:
Five years ago, we pioneered open sharing and collaboration with the Delta Sharing protocol - it is now the most widely adopted open protocol for secure zero-copy data sharing used by thousands of enterprises. Building on this momentum, last week, we announced OpenSharing, the next evolution of Delta Sharing. OpenSharing, now a project of the Linux Foundation, introduces the first open, vendor-neutral protocol for securely sharing AI assets, including Agent Skills, AI models, and unstructured data.
We're now announcing a number of capabilities to enable collaboration:
Unity Catalog continues evolving as the industry’s only unified governance layer, the foundation for secure, intelligent, and business-aware data platforms. Whether you’re building AI agents, delivering BI dashboards, or sharing data across organizations, Unity Catalog connects it all through a single, open catalog.
To get started, follow the Unity Catalog guides for AWS, Azure, and GCP.
Register for Data + AI Summit and explore our Governance and Security Sessions.
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