Today marks a major milestone in our partnership with Databricks — one built on a shared belief: that context and trust are the foundation for any meaningful AI transformation.
At the 2025 Data + AI Summit, we’re excited to announce that Atlan is launching Data Quality Studio for Databricks, and will be a launch partner for Databricks’ newly announced Unity Catalog Metrics and Managed Iceberg. Together, we’re helping modern data teams scale trusted, production-grade AI with a unified foundation of context, collaboration, and control.
And customers are already seeing the impact. Over the past year, our joint customer base has grown 3x, with organizations like Fox, General Motors, Nubank, Mastercard, and Ralph Lauren choosing Atlan + Databricks to power their AI-native journeys.
1. Data Quality Studio for Databricks #
AI breaks when it runs on untrusted data. That’s why we’re launching Data Quality Studio for Databricks — a native integration that brings business-defined quality checks directly into the lakehouse.
Unlike traditional tools that focus on technical checks, Data Quality Studio puts the business in the driver’s seat. Teams can define what “good” looks like — whether it’s freshness, null thresholds, or custom KPIs — using plain language or SQL. These checks are executed in Databricks, without moving data or introducing new infrastructure.
“AI breaks when it runs on untrusted data,” said Prukalpa Sankar, Co-founder of Atlan. “With Data Quality Studio, quality expectations are defined by the people who understand the business need — and run natively in Databricks. Together, Atlan and Databricks are empowering customers to move faster with trusted AI.”
2. Launch Partner for Databricks Unity Catalog Metrics #
With the launch of Unity Catalog Metrics, Databricks has introduced a semantic layer for standardized, reusable KPIs. As a launch partner, Atlan brings these metrics to life — turning static definitions into living assets.
We enrich every metric with deep business context and end-to-end lineage, so teams can finally answer the question: “Where did this number come from?” From source table to dashboard, every step is visible, verifiable, and trusted.
This is more than documentation — it’s the metadata layer that fuels confident decisions, governed BI, and intelligent AI.
3. Launch Partner for Databricks Managed Iceberg #
Databricks and Atlan are doubling down on open formats, giving customers the interoperability and flexibility they need to power a variety of metadata and governance use cases for analytics and AI.
As a launch partner for Managed Iceberg, Atlan’s Metadata Lakehouse will now integrate more deeply with the Databricks Lakehouse. This unlocks powerful use cases like metadata analytics, AI policy enforcement, and governance observability — all inside Databricks.
It also means AI agents like Databricks Genies and Genie Rooms can access rich metadata context from Atlan — bringing explainability and control to every intelligent system.
💬 From the Frontlines: General Motors’ Take #
“If we didn’t have AI in our arsenal, we could find ourselves at a competitive disadvantage. Unity Catalog worked out of the box for us… and Atlan gave us visibility from the cloud all the way back to our on-prem.” — Brian Ames, leading AI/ML at General Motors.
This is the kind of trusted foundation that Atlan and Databricks are delivering — one that doesn’t just support AI experimentation, but accelerates production at scale.
One Team, One Mission: Context for the AI-Native Enterprise #
These launches are more than product features. They’re proof of a shared vision: Atlan and Databricks are collaboratively building the operating system for context and trust across the AI-native enterprise — one where metadata and governance aren’t afterthoughts, but the foundation for innovation.
Databricks powers the engine for data and AI. Atlan unifies and activates the metadata layer to make context trusted, transparent, and usable across the enterprise with deep collaboration across teams.