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Databricks

Why Talent Transformation Is the Missing Focus of Enterprise AI Public Health Intelligence Shouldn't Require a Data Scientist Mean Time to Detect Is a Data Access Problem First-party audience data is the ad sales relationship now Rethinking Distributed Systems for Serverless Performance and Reliability The AI Scaling Gap Hiding in Digital Native Companies 10 trillion samples a day: Scaling beyond traditional monitoring infra at Databricks AI success starts with clean data, not just better models How nOps Rebuilt Their Cloud Optimization Platform on Databricks Lakebase, and Why Other ISVs Should Too Peril Predicts: Precision Payouts for a Volatile World The foundation of AI scalability: one team, one platform, one operating model The Federal Data Paradox: Rich in Data, Poor in Access Driving Budapest Forward: How BKK Uses Databricks to Transform City Mobility LLM Vs AI: A Practical Guide to Differences, Use Cases, and Tools Model Risk Governance Is Not the Same as Risk Intelligence Generative AI for Business: A Complete Strategy and Implementation Guide Data Science vs Data Engineering: Choosing Analysis or Infrastructure AI Applications: Tools, Use Cases, and Platforms MLOps vs DevOps: A Practical Guide for Data Scientists and IT Teams Top Data Warehouse Tools For Modern Data Analytics Unlocking SAP Business Context in Databricks with Semantic Metadata Delta Sharing The marketing activation gap has a fix: Databricks and Stitch partner to turn data infrastructure into marketing performance Alert Fatigue Is a Business Risk Backstage with Lakebase Shipping Faster isn’t Learning Faster Why Your OEE Dashboard Is Lying to You The Turbine That Tried to Tell You It Was Failing Predicting Readmissions Isn't Enough. Acting in Time Is. Clinical Trials Run Longer Than They Have To. That's a Patient Problem Network Quality Is a Revenue Problem, Not a Technical One Shelf Availability Starts with Better Demand Visibility When Predicting the Next Hit Requires More Than Intuition Approximate Answers, Exact Decisions: New Sketch Functions for Analytics Companies Winning with AI Built the Data Layer First Rethinking SQL ETL for modern data platforms Stripe data now available on Databricks via Databricks Marketplace Databricks and Stripe Projects: Infrastructure Built for Agents Agents are ready but your architecture probably isn't Interoperability Between Unity Catalog and Google BigQuery via Catalog Federation Built In, Not Bolted On: What AI-Native Actually Means in Cybersecurity Operationalizing AI for public sector fraud prevention From months to minutes: Building real-time clinical data pipelines with natural language Agentic Data Engineering with Genie Code and Lakeflow Securely send first-party conversion signals with Snapchat Conversions API on Databricks Marketplace How leading tech companies are killing the builder’s tax with Lakebase Inside one of the first production deployments of Lakebase: LangGuard's agentic workflow governance engine The next generation of Databricks Genie Model Risk Management in 2026: A Banker’s Guide to the Revised Interagency Guidance OpenAI GPT-5.5 now available on Databricks, fully-governed through Unity AI Gateway Operational databases: How they work and when to use them Databricks partners with OpenAI on GPT-5.5 Announcing the Public Preview of Lakeflow Designer Are LLM agents good at join order optimization? 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Expanded interoperability with Unity Catalog Open APIs
2026-05-15 · via Databricks

Unity Catalog was designed for the open lakehouse. Previously, data teams were stuck in silos, often forced to duplicate data across platforms just to use the tools they wanted. Every new platform or tool meant copying datasets, rebuilding access policies from scratch, and keeping everything in sync. The result was increased costs from redundant storage, policies that drifted out of sync, and fragmented data access and discovery.

When we open sourced Unity Catalog and launched Open APIs, we broke down the silos that previously kept customers locked-in. Enterprises could finally keep one copy of data, use any compute engine, and govern everything from one place. The UC ecosystem has thrived since. Today, thousands of customers use Unity Catalog to govern and access Delta Lake and Apache Iceberg tables, with dozens of integrations in the growing Unity Catalog ecosystem — from Apache Spark and Trino to DuckDB and Confluent Tableflow.

External Access to Managed Tables, Now in Beta

UC managed tables are where openness meets performance. These advanced tables use Predictive Optimization and Liquid Clustering to automatically tune data layouts, run compaction and vacuuming, and keep statistics fresh — delivering up to 20× faster queries and 50% lower storage costs, while staying fully accessible through open APIs.

Now in Beta, external engines, such as Apache Spark, Flink, and DuckDB, can create and write to UC managed Delta tables with centralized governance and automatic optimizations.

With the Beta, external engines can:

  • Create managed tables — Stand up new UC managed tables directly from an external engine.
  • Batch read and write — Read and write to managed tables with full transactional safety.
  • Stream to and from managed tables — Use managed tables as both a streaming source and sink, enabling end-to-end real-time pipelines on Apache Spark.

Because every operation flows through UC managed tables built on catalog commits, you get serialized commits that prevent log corruption and complete auditability of every read and write. Predictive Optimization continues to run seamlessly, even on tables accessed by external engines. Catalog commits also lay the groundwork for features like multi-statement, multi-table transactions that require a centralized commit coordinator.

The thriving UC ecosystem is continuing to grow as engines expand support for external access to managed tables. Delta Kernel — the open source Java and Rust library for reading, writing, and committing to Delta tables — abstracts the low-level protocol details so connector developers can focus on UC integration, not Delta implementation. Apache Spark, Delta Flink, and DuckDB have all leveraged Delta Kernel to support external writes to UC managed tables and integrate with catalog-managed commits, and the ecosystem continues to grow. By handling the low-level protocol complexity, Delta Kernel makes it straightforward for any engine to integrate with Unity Catalog which contributes to a growing ecosystem of connectors.

Secure External Access Made Possible By Credential Vending

For an external engine to access data in UC, it needs a secure way to authenticate and get scoped access to cloud storage without requiring broad, static permissions or credentials tied to a specific account. Unity Catalog handles this through credential vending, which is now generally available (GA): UC issues short-lived, scoped credentials to external engines on demand, with access policies enforced centrally.

Thousands of customers have used UC Open APIs and two additions make it production-ready at enterprise scale. External engines can now authenticate to UC using machine-to-machine (M2M) OAuth, meeting enterprise security requirements without relying on personalized access tokens (PATs), which are per-user, long-lived, and hard to rotate. And credentials are refreshed automatically by engines via the UC credential vending APIs, so pipelines that run for hours complete reliably without tokens expiring mid-job.

Query execution with credential vending
Query execution with credential vending using an external compute engine

With credential vending, enterprises can read, write, and create managed and external tables in Unity Catalog from any compatible engine or tool. These credentials are short-lived, scoped to the requested resource, and governed by UC privileges. This means your platform team retains full control over which principals can access data externally and what they can do with it.

With Unity Catalog’s Open APIs, we've empowered our teams to use their preferred tools while maintaining governance and data consistency. We can leverage the benefits of managed tables within a truly interoperable data and AI platform that works across multiple compute engines.— Sudipta Das, Director of Enterprise Data Operations at PepsiCo

Credential Vending for Volumes

Credential vending extends not only to tables but also unstructured data. Volume credential vending is now in Public Preview, so external clients can request temporary, scoped credentials to access images, PDFs, and videos stored in volumes with Unity Catalog governance. The same access control model, audit trail, and scoped credentials apply whether you're querying a table or processing a raw video file externally.

What's Next?

We're continuing to invest in making external access more capable. Credential vending today governs coarse-grained access controls for external engines. We've also developed functionality to enforce attribute-based access controls (ABAC) for external reads, which makes governance fine-grained. This makes it possible to enforce row and column level ABAC policies when UC managed tables are read rom external engines.

Get Started Today

To get started with credential vending, see our documentation. To use the Beta of external access to managed Delta tables:

  1. Enroll in "External Access to Unity Catalog Managed Delta Table" in the Databricks preview portal (see Manage Databricks previews
  2. Enable external data access on your metastore and grant EXTERNAL_USE_SCHEMA on the schema containing the tables you want to access.
  3. Create a new UC managed table. To move existing data, see the migration guide for converting external tables to managed.
  4. Use Delta-Spark 4.2 with Unity Catalog 0.4.1 to create, read, and write to managed tables from external compute. See the external access documentation.

Join us at Data and AI Summit 2026

Data and AI Summit 2026 is almost here! Join us June 15-18, 2026 at the Moscone Center in San Francisco, California to learn how leading organizations are using Unity Catalog to govern data and AI across engines. Register today to get a first look at what’s coming next for open, unified governance.