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What’s new with Databricks Unity Catalog at Data + AI Summit 2025

Unifying data and AI governance across formats, clouds, and teams

What's new in UC at DAIS

Published: June 12, 2025

Product7 min read

Summary

• Unity Catalog unifies Delta Lake and Apache Iceberg™, eliminating format silos to provide seamless governance and interoperability across clouds and engines.
• Databricks is extending Unity Catalog to knowledge workers by making business metrics first-class data assets with Unity Catalog Metrics and introducing a curated internal marketplace that helps teams easily discover high-value data and AI assets organized by domain.
• Enhanced governance controls like attribute-based access control and data quality monitoring scale secure data management across the enterprise.

Four years ago, Databricks saw tremendous complexity in the data landscape: separate catalogs for each platform, siloed governance tools across clouds, and no unified way to secure AI assets. We pioneered Unified Governance by launching Unity Catalog, an open, flexible catalog layer to manage access, lineage, auditing, and discovery across all data and AI assets.

Today, Unity Catalog has become the foundation of the Databricks Data Intelligence Platform and the industry’s only unified governance solution for data and AI across formats, clouds, and engines. From open data sharing to fine-grained security and knowledge governance, Unity Catalog helps organizations bring context, control, and confidence to their data estate.

At this year’s Data + AI Summit, we’re announcing major innovations across Unity Catalog, delivering the best catalog for Apache Iceberg™, new business user experiences, and intelligent governance to protect sensitive data and ensure trusted data quality at scale.

Here’s what’s new.

The Best Catalog for Apache Iceberg™

Organizations adopting a lakehouse are often forced to choose between Delta Lake and Apache Iceberg™. That choice creates artificial silos: restricting access to the data and AI tools that teams can use, fragmenting governance, and locking metadata into format-specific catalogs.

Unity Catalog eliminates the need to choose. Built on open standards, Unity Catalog is the only unified catalog that works seamlessly across formats, engines, and clouds, making it the foundation of the open lakehouse. Over the past year, following the acquisition of Tabular, we’ve invested deeply in Apache Iceberg to extend this vision. We’re excited to announce:

  • Full support for the Iceberg REST Catalog API, allowing external engines to read (Generally Available) and write (Public Preview) to Unity Catalog–managed Iceberg tables. This is a major differentiator in the market, eliminating format lock-in and enabling full interoperability unmatched by any other solution. 
  • Iceberg managed tables are now in Public Preview, delivering best-in-class price and performance, liquid clustering, predictive optimization, and full integration with Databricks and across external engines, including Trino, Snowflake, and Amazon EMR.
  • Iceberg catalog federation is in Public Preview, enabling you to govern and query Iceberg tables managed in AWS Glue, Hive Metastore, and Snowflake Horizon without copying data.
  • Delta Sharing for Iceberg is now in Private Preview, allowing you to share Unity Catalog tables and Delta tables with any recipient using Delta Sharing and consume them in any client that supports the Iceberg REST Catalog API.

Together, these capabilities break down format silos and set Unity Catalog apart as the only catalog that delivers truly open, unified governance and interoperability. Check out our blog on Iceberg support to learn more about these announcements. 

Unity Catalog open integrations

Expanding Unity Catalog to business users

Data platforms shouldn’t stop at the technical user. Business users need a clear, consistent way to find, trust, and work with data. Unity Catalog now offers a unified foundation for business context to bridge the gap between data and business teams. 

Unity Catalog Metrics: One semantic layer for all data and AI workloads

Inconsistent metric definitions across tools and teams have long caused confusion, misalignment, and a lack of trust in data. Unity Catalog Metrics, now in Public Preview on AWS, Azure, and GCP and Generally Available later this summer, solves this by making business metrics first-class assets in the lakehouse. Unlike metrics defined only in the BI layer, which limit reuse and integration, defining metrics at the data layer makes business semantics reusable across all workloads, like dashboards, AI models, and data engineering jobs. Unity Catalog Metrics are also fully addressable via SQL to ensure that everyone in the organization can have the same view of metrics, irrespective of what tool they choose.

  • Define once, use everywhere: Create metrics once in Unity Catalog and use them across AI/BI Dashboards, Genie, Notebooks, SQL, and Lakeflow jobs. Upcoming integrations will extend support to BI tools like Tableau, Hex, Sigma, ThoughtSpot, Omni and observability tools like Anomalo and Monte Carlo.
  • Governed and auditable by default: Certified metrics come with auditing and lineage out of the box, enabling trusted, compliant insights across teams.

Unity Catalog Metrics Partners

"Unity Catalog Metrics gives us a central place to define business KPIs and standardize semantics across teams, ensuring everyone works from the same trusted definitions across dashboards, SQL, and AI applications."
— Richard Masters, Vice President, Data & AI, Virgin Atlantic
"Unity Catalog Metrics represents an exciting opportunity for Tableau customers to leverage the value of centralized governance with Databricks Unity Catalog. Through our deep integration and expanding roadmap with Databricks, we’re thrilled to help remove the friction for our customers in leveraging Databricks to define their core business metrics."
— Nicolas Brisoux, Sr. Director Product Management, Tableau

New curated discovery experiences with intelligent insights

To fully empower business users, you must make trusted data easy to find, understand, and use. Unity Catalog is extending its business-aware governance with a new Discover experience, now in Private Preview, a curated internal marketplace of certified data products organized by business domains like Sales, Marketing, or Finance. 

AI-powered recommendations and data steward curation help surface the highest-value assets, such as metrics, dashboards, tables, AI agents, and Genie spaces that are enriched with documentation, ownership, and usage insights. New intelligent signals highlight data quality, usage patterns, relationships, and certification status, helping users quickly assess trust and relevance. Plus, with Databricks Assistant built in, users can ask natural language questions and get clear, context-aware answers based on governed metrics.

Unity Catalog Discover UI

We’re also introducing new intelligent capabilities across Databricks to make data discovery easier and more intuitive, wherever users work in the platform. Powered by Unity Catalog, these features help teams find trusted data faster and understand its context at a glance.

  • Domains (Coming soon): Organize data by business area to align discovery with the organization's operations.
  • Certifications and Deprecation Tags (Beta): Signal data trust and business relevance across datasets, metrics, and dashboards. Tagged assets prominently display their status in authoring surfaces like the SQL editor, keeping data quality signals visible throughout the user workflow. Certifications and deprecation tags are available as a part of Tag Policies Beta. 
  • Request for Access (Public Preview): To streamline delivery, users can instantly request data access directly to the asset.

Additional advanced governance capabilities now available 

High-leverage governance with scalable, attribute-driven controls

Scaling data governance becomes increasingly challenging as organizations grow, with more users, teams, and data assets to manage. Static policies and manual controls can’t keep up, leading to governance gaps, security risks, and operational bottlenecks. 

To address these challenges, Unity Catalog now provides intelligent automation and flexible, scalable controls to classify sensitive data, enforce policy consistently, and accelerate secure data access across the lakehouse. 

  • Attribute-based access control (ABAC): Define flexible access policies using tags that can be applied at the catalog, schema, or table level. ABAC is available in Beta for row and column-level security on AWS, Azure, and GCP

  • Tag policies: Tag policies enforce a governance layer for how tags are created, assigned, and used across Databricks. These account-level policies ensure tags remain consistent and trusted, supporting everything from data classification to cost attribution. Tag policies are available in Beta on AWS, Azure, and GCP

  • Data classification: Intelligently detect and tag sensitive data across Unity Catalog. New data is scanned within 24 hours to automatically detect new PII, minimizing manual effort and allowing teams to stay on top of data access. When used with ABAC, Data classification automatically protects sensitive data based on your access control policies. Data classification is available in Beta on AWS, Azure, and GCP

“Implementing column masking across more than 5,000 tables used to be an enormous manual effort. With ABAC, we’re able to apply consistent policies dynamically, drastically improving both speed and governance.” 
— Ramesh Balasubramanyan, Databricks Admin, SAIF
“Databricks Data Classification has been a game-changer in our data privacy and security strategy. Paired with ABAC, it enables us to automatically secure sensitive data without restricting the data that our analysts need. The biggest benefit has been speed, with automated classification and masking significantly reducing manual overhead, freeing up our resourcing and saving our team countless hours each week.”
— Mary Tesfay, Data & Analytics Lead, Corp IT, Navitas

Automated data quality monitoring at scale

Unity Catalog now intelligently detects and helps resolve data quality issues across all your tables with data quality monitoring, available in beta on AWS, Azure, and GCP. Data quality monitoring checks freshness—how recently data has been updated—and completeness—whether data volumes are as expected—using data intelligence across entire schemas. Consumers are able to understand the health of data at a glance with health indicators, while data owners can understand the priority of issues based on downstream lineage, uncover the root cause, and set alerts using built-in logging and dashboards. 

Data quality monitoring UI

Get started with Unity Catalog, the foundation of Data Intelligence

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

Watch the Data + AI Summit 2025 keynote from Matei Zaharia, Co-founder and Chief Technology Officer at Databricks, to learn more about these recent announcements. 

Register for Data + AI Summit and explore the data and AI governance track

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