4 years in the past, Databricks noticed great complexity within the knowledge panorama: separate catalogs for every platform, siloed governance instruments throughout clouds, and no unified technique to safe AI property. We pioneered Unified Governance by launching Unity Catalog, an open, versatile catalog layer to handle entry, lineage, auditing, and discovery throughout all knowledge and AI property.
Right now, Unity Catalog has turn out to be the inspiration of the Databricks Information Intelligence Platform and the trade’s solely unified governance answer for knowledge and AI throughout codecs, clouds, and engines. From open knowledge sharing to fine-grained safety and data governance, Unity Catalog helps organizations deliver context, management, and confidence to their knowledge property.
At this yr’s Information + AI Summit, we’re asserting main improvements throughout Unity Catalog, delivering the most effective catalog for Apache Iceberg™, new enterprise person experiences, and clever governance to guard delicate knowledge and guarantee trusted knowledge high quality at scale.
Right here’s what’s new.
The Greatest Catalog for Apache Iceberg™
Organizations adopting a lakehouse are sometimes pressured to decide on between Delta Lake and Apache Iceberg™. That selection creates synthetic silos: limiting entry to the info and AI instruments that groups can use, fragmenting governance, and locking metadata into format-specific catalogs.
Unity Catalog eliminates the necessity to decide on. Constructed on open requirements, Unity Catalog is the one unified catalog that works seamlessly throughout codecs, engines, and clouds, making it the inspiration of the open lakehouse. Over the previous yr, following the acquisition of Tabular, we’ve invested deeply in Apache Iceberg to increase this imaginative and prescient. We’re excited to announce:
- Full assist for the Iceberg REST Catalog API, permitting exterior engines to learn (Usually Out there) and write (Public Preview) to Unity Catalog–managed Iceberg tables. It is a main differentiator available in the market, eliminating format lock-in and enabling full interoperability unmatched by another answer.
- Iceberg managed tables at the moment are in Public Preview, delivering best-in-class value and efficiency, liquid clustering, predictive optimization, and full integration with Databricks and throughout exterior engines, together with Trino, Snowflake, and Amazon EMR.
- Iceberg catalog federation is in Public Preview, enabling you to control and question Iceberg tables managed in AWS Glue, Hive Metastore, and Snowflake Horizon with out copying knowledge.
- Delta Sharing for Iceberg is now in Non-public Preview, permitting you to share Unity Catalog tables and Delta tables with any recipient utilizing Delta Sharing and devour them in any consumer that helps the Iceberg REST Catalog API.
Collectively, these capabilities break down format silos and set Unity Catalog aside as the one catalog that delivers actually open, unified governance and interoperability. Try our weblog on Iceberg assist to be taught extra about these bulletins.
Increasing Unity Catalog to enterprise customers
Information platforms shouldn’t cease on the technical person. Enterprise customers want a transparent, constant technique to discover, belief, and work with knowledge. Unity Catalog now gives a unified basis for enterprise context to bridge the hole between knowledge and enterprise groups.
Unity Catalog Metrics: One semantic layer for all knowledge and AI workloads
Inconsistent metric definitions throughout instruments and groups have lengthy brought on confusion, misalignment, and an absence of belief in knowledge. Unity Catalog Metrics, now in Public Preview on AWS, Azure, and GCP and Usually Out there later this summer time, solves this by making enterprise metrics first-class property within the lakehouse. In contrast to metrics outlined solely within the BI layer, which restrict reuse and integration, defining metrics on the knowledge layer makes enterprise semantics reusable throughout all workloads, like dashboards, AI fashions, and knowledge engineering jobs. Unity Catalog Metrics are additionally totally addressable through SQL to make sure that everybody within the group can have the identical view of metrics, regardless of what instrument they select.
- Outline as soon as, use in all places: Create metrics as soon as in Unity Catalog and use them throughout AI/BI Dashboards, Genie, Notebooks, SQL, and Lakeflow jobs. Upcoming integrations will lengthen assist to BI instruments like Tableau, Hex, Sigma, ThoughtSpot, Omni and observability instruments like Anomalo and Monte Carlo.
- Ruled and auditable by default: Licensed metrics include auditing and lineage out of the field, enabling trusted, compliant insights throughout groups.
“Unity Catalog Metrics offers us a central place to outline enterprise KPIs and standardize semantics throughout groups, making certain everybody works from the identical trusted definitions throughout dashboards, SQL, and AI purposes.”
— Richard Masters, Vice President, Information & AI, Virgin Atlantic
“Unity Catalog Metrics represents an thrilling alternative for Tableau prospects to leverage the worth of centralized governance with Databricks Unity Catalog. By means of our deep integration and increasing roadmap with Databricks, we’re thrilled to assist take away the friction for our prospects in leveraging Databricks to outline their core enterprise metrics.”
— Nicolas Brisoux, Sr. Director Product Administration, Tableau
New curated discovery experiences with clever insights
To totally empower enterprise customers, you should make trusted knowledge simple to search out, perceive, and use. Unity Catalog is extending its business-aware governance with a brand new Uncover expertise, now in Non-public Preview, a curated inner market of licensed knowledge merchandise organized by enterprise domains like Gross sales, Advertising and marketing, or Finance.
AI-powered suggestions and knowledge steward curation assist floor the highest-value property, reminiscent of metrics, dashboards, tables, AI brokers, and Genie areas which are enriched with documentation, possession, and utilization insights. New clever indicators spotlight knowledge high quality, utilization patterns, relationships, and certification standing, serving to customers rapidly assess belief and relevance. Plus, with Databricks Assistant inbuilt, customers can ask pure language questions and get clear, context-aware solutions primarily based on ruled metrics.
We’re additionally introducing new clever capabilities throughout Databricks to make knowledge discovery simpler and extra intuitive, wherever customers work within the platform. Powered by Unity Catalog, these options assist groups discover trusted knowledge sooner and perceive its context at a look.
- Domains (Coming quickly): Manage knowledge by enterprise space to align discovery with the group’s operations.
- Certifications and Deprecation Tags (Beta): Sign knowledge belief and enterprise relevance throughout datasets, metrics, and dashboards. Tagged property prominently show their standing in authoring surfaces just like the SQL editor, preserving knowledge high quality indicators seen all through the person workflow. Certifications and deprecation tags can be found as part of Tag Insurance policies Beta.
- Request for Entry (Public Preview): To streamline supply, customers can immediately request knowledge entry on to the asset.
Further superior governance capabilities now out there
Excessive-leverage governance with scalable, attribute-driven controls
Scaling knowledge governance turns into more and more difficult as organizations develop, with extra customers, groups, and knowledge property to handle. Static insurance policies and guide controls can’t sustain, resulting in governance gaps, safety dangers, and operational bottlenecks.
To handle these challenges, Unity Catalog now offers clever automation and versatile, scalable controls to categorise delicate knowledge, implement coverage persistently, and speed up safe knowledge entry throughout the lakehouse.
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Attribute-based entry management (ABAC): Outline versatile entry insurance policies utilizing tags that may be utilized on the catalog, schema, or desk degree. ABAC is offered in Beta for row and column-level safety on AWS, Azure, and GCP.
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Tag insurance policies: Tag insurance policies implement a governance layer for a way tags are created, assigned, and used throughout Databricks. These account-level insurance policies guarantee tags stay constant and trusted, supporting all the pieces from knowledge classification to value attribution. Tag insurance policies can be found in Beta on AWS, Azure, and GCP.
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Information classification: Intelligently detect and tag delicate knowledge throughout Unity Catalog. New knowledge is scanned inside 24 hours to mechanically detect new PII, minimizing guide effort and permitting groups to remain on high of information entry. When used with ABAC, Information classification mechanically protects delicate knowledge primarily based in your entry management insurance policies. Information classification is offered in Beta on AWS, Azure, and GCP.
“Implementing column masking throughout greater than 5,000 tables was an unlimited guide effort. With ABAC, we’re in a position to apply constant insurance policies dynamically, drastically enhancing each pace and governance.”
— Ramesh Balasubramanyan, Databricks Admin, SAIF
“Databricks Information Classification has been a game-changer in our knowledge privateness and safety technique. Paired with ABAC, it allows us to mechanically safe delicate knowledge with out limiting the info that our analysts want. The largest profit has been pace, with automated classification and masking considerably lowering guide overhead, releasing up our resourcing and saving our staff numerous hours every week.”
— Mary Tesfay, Information & Analytics Lead, Corp IT, Navitas
Automated knowledge high quality monitoring at scale
Unity Catalog now intelligently detects and helps resolve knowledge high quality points throughout all of your tables with knowledge high quality monitoring, out there in beta on AWS, Azure, and GCP. Information high quality monitoring checks freshness—how not too long ago knowledge has been up to date—and completeness—whether or not knowledge volumes are as anticipated—utilizing knowledge intelligence throughout total schemas. Shoppers are in a position to perceive the well being of information at a look with well being indicators, whereas knowledge house owners can perceive the precedence of points primarily based on downstream lineage, uncover the basis trigger, and set alerts utilizing built-in logging and dashboards.
Get began with Unity Catalog, the inspiration of Information Intelligence
Unity Catalog continues evolving because the trade’s solely unified governance layer, the inspiration for safe, clever, and business-aware knowledge platforms. Whether or not you’re constructing AI brokers, delivering BI dashboards, or sharing knowledge throughout organizations, Unity Catalog connects all of it by way of a single, open catalog.
To get began, comply with the Unity Catalog guides for AWS, Azure, and GCP.
Watch the Information + AI Summit 2025 keynote from Matei Zaharia, Co-founder and Chief Expertise Officer at Databricks, to be taught extra about these current bulletins.
Register for Information + AI Summit and discover the knowledge and AI governance monitor
