Unity Catalog vs Collibra

Summary

• Unity Catalog is "the unified governance layer for data and AI built into Databricks". Collibra describes itself as "the enterprise AI control plane governing context and ensuring control across every source, model and agent".
• Unity Catalog operates beneath data and AI interactions in Databricks workspaces: it enforces access control, tracks lineage, and logs activity as assets are used.
• Collibra documents an integration with Unity Catalog that runs only through Edge. It ingests Unity Catalog metadata, retrieves technical lineage, and can write Collibra attribute values back to Unity Catalog tags.
• Because the integration is documented, the two can be used together. The better fit depends on where your data lives and which governance tools your teams already run.

Unity Catalog vs Collibra

Unity Catalog and Collibra both govern data and metadata, from different starting points. Unity Catalog is built into Databricks and applies governance as assets are queried and used in a workspace. Collibra is a separate platform that connects to Databricks through a documented integration. The practical difference is where each one sits: Unity Catalog inside Databricks, Collibra alongside it.

What does Unity Catalog do?

The Databricks docs say that, when enabled for a workspace, Unity Catalog "operates beneath every data and AI interaction in your workspaces automatically: enforcing access control when you query a table or call a model, tracking lineage as data and AI assets are used, logging activity for auditing, and more." You work with governed objects through Catalog Explorer, SQL, the Databricks CLI, and REST APIs. Governance also reaches beyond managed tables: external tables and volumes (where Unity Catalog handles governance only), foreign catalogs through Lakehouse Federation (governed, read-only access to external data), and external lineage assets. Unity Catalog is also available as an open-source implementation.

What does Collibra document for Databricks?

Collibra's docs state: "You can integrate Databricks Unity Catalog only via Edge." The integration ingests Databricks databases, schemas, tables, database views, metric views, columns, volumes, directories, files, and notebooks, and you can synchronize manually or on a schedule. Outbound synchronization "propagates attribute values from Collibra to tags in Databricks Unity Catalog" for Database, Schema, Table, Database View, and Column assets. A separate Technical Lineage for Databricks Unity Catalog capability "allows Collibra Data Lineage to retrieve lineage information from your data source", and its preflight checks require SELECT on system.access.column_lineage.
Collibra also documents Collibra Protect, which "secures sensitive data and grants varying levels of access to specific groups of people through no-code policies". Per Collibra, data access standards created in Protect result in column-based policies on Databricks, and row filters in data access rules result in row-based policies on Databricks.

Unity Catalog vs Collibra: how they compare

Area	Unity Catalog (Databricks docs)	Collibra (Collibra docs)
Where it sits	Built into Databricks	A separate platform; the Databricks Unity Catalog integration runs only via Edge
Metadata	Securable objects such as tables, views, volumes, functions, models, and services in a catalog.schema.object namespace	Ingests databases, schemas, tables, database views, metric views, columns, volumes, directories, files, and notebooks
Lineage	Captured automatically for queries run on Databricks, down to the column level	A Technical Lineage for Databricks Unity Catalog capability retrieves lineage information
Access control	Privileges, attribute-based policies, row filters, column masks, and workspace bindings	Protect applies column-based and row-based policies on Databricks
Classification	Data Classification uses an agentic AI system to classify and tag sensitive data in tables	An optional JDBC connection profiles and classifies the integrated data
Tags	Governed tags drive attribute-based policies	Outbound synchronization writes Collibra attribute values to Unity Catalog tags

How do you use the two together?

Collibra's setup steps are to create a Databricks connection, add the Databricks Unity Catalog capability to your Edge connections, and synchronize inbound metadata. Technical lineage is a second capability with its own Databricks Workspace connection. Protect is defined in Collibra: its FAQ states that Protect "can't import or synchronize policies created directly in the data source" and that synchronization is one-way, from Collibra to the data source. In Unity Catalog, row filters and column masks restrict "the rows and column values a user can see at query time", and Databricks recommends ABAC policies for consistent filtering and masking across many tables.

FAQs

Does Unity Catalog replace Collibra?

That depends on your requirements. Unity Catalog governs the data and AI assets that Databricks workspaces use. Collibra describes governing context "across every source, model and agent", and it documents an integration that ingests Unity Catalog metadata and lineage. Teams that run only Databricks can start with the Unity Catalog capabilities above.

Can I use both together?

Yes. Collibra documents inbound synchronization of Unity Catalog metadata, technical lineage, and outbound synchronization of attribute values to Unity Catalog tags, all through Edge.

Does Collibra read lineage from Databricks?

Collibra documents a Technical Lineage for Databricks Unity Catalog capability. Its preflight checks list SELECT on system.access.column_lineage as mandatory, plus SELECT on system.access.table_lineage if you enable the table lineage option.

Does Unity Catalog govern data outside Databricks?

It governs external tables and volumes, foreign catalogs through Lakehouse Federation, and external lineage assets that you register in Unity Catalog. Lakehouse Federation access is read-only.