Informatica deepens Databricks tie-up with new data tools
Mon, 25th May 2026
Informatica has added four new data management and governance integrations for Databricks, extending the companies' partnership across AI agents, transactional data, master data and data cataloguing.
The additions include headless data management for Databricks Agent Bricks, a connector for Databricks Lakebase, a way to publish master data records into the Databricks lakehouse, and the extraction of governance tags from Unity Catalog into Informatica's data catalogue.
The first product links Informatica Intelligent Data Management Cloud with Databricks Agent Bricks through Model Context Protocol servers. The setup allows companies to call microservices such as metadata search and address validation directly within agent workflows, without building custom integrations.
The integration is in private preview and is expected to become generally available in a summer 2026 release. It will also be offered through the Databricks Marketplace.
The second product is a named connector for Databricks Lakebase, designed to ingest, transform and govern transactional online transaction processing data moving into Lakebase for use with Agent Bricks.
The connector is scheduled for release in October 2026 and is positioned as a tool for handling operational data used in production AI agent workflows.
A third addition focuses on master data. The MDM Extension for Databricks is designed to let companies publish so-called golden records from Informatica's Master Data Management platform directly into Databricks SQL.
The extension includes pre-configured schemas for customer, supplier, product and location data. It also supports the extraction of master data hierarchies and relationships into the Databricks environment.
The fourth announcement is already available as part of Informatica's April 2026 release. Cloud Data Governance and Catalog can now extract governance tags from Databricks Unity Catalog and surface them in the Informatica Data Catalog.
Governance focus
The link is aimed at data stewards working across both platforms and is intended to federate governance information between the systems without duplicating stewardship work.
The latest announcements show how data software suppliers are positioning governance and master data tools closer to AI development environments. As more companies seek to deploy AI agents into business processes, vendors are placing greater emphasis on data lineage, metadata access, and controls over operational and reference data.
Informatica framed its partnership with Databricks around demand for trusted, governed data. "The organizations that win the AI race will be those that put trusted, governed data in front of their agents from day one," said Rik Tamm-Daniels, Vice President, Ecosystems and Technology, Informatica from Salesforce.
"Together with Databricks, we're building the data foundation the agentic enterprise demands."
Databricks also linked the expanded tie-up to customer demand for governed data in production AI systems. "Customers consistently ask us to help them operationalize agents with well governed data that can scale in production," said Stephen Orban, Senior Vice President, Product Ecosystem & Partnerships, Databricks.
"Our deepening partnership with Informatica gives joint customers the high-quality data foundation they need to deploy AI agents reliably and securely across the enterprise."
Broader tie-up
The announcements also underline Informatica's effort to align its software with open and shared standards emerging around AI systems. Model Context Protocol, which underpins the new headless data management integration, is gaining traction as a way for AI agents to interact with external tools and services.
For Databricks, the additions broaden the set of enterprise data management functions available around its platform, particularly in transactional data handling, master data publishing and governance metadata exchange. Large organisations often need to connect these parts of the data stack before moving AI projects into day-to-day operations.
One of the clearest examples is the new Unity Catalog tag extraction feature, which addresses a practical issue for large data teams: how to maintain governance context across more than one catalogue. The feature brings those tags into Informatica's own catalogue to create a broader enterprise view of governed data.
Tamm-Daniels also highlighted that catalogue strategy. "We're embracing Unity Catalog and adding the holistic interoperability enterprise customers are asking for to securely democratize all their enterprise data assets," said Rik Tamm-Daniels, Vice President, Ecosystem & Technology Alliances, Informatica.
"The extraction of tags from Unity Catalog showcases CDGC as the 'Catalog of Catalogs' in action: from governance of the Databricks Lakehouse, to sources across enterprise data estate, Informatica unifies it into a single, trusted enterprise view."