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Unity Catalog in Databricks Cheat Sheet

Unity Catalog in Databricks Cheat Sheet

Back to Data Engineering
Updated 2026-04-21

Unity Catalog is Databricks' unified governance layer for data and AI assets, built on a metastore and a three-level namespace (catalog → schema → object). It standardizes access control, auditing, lineage, and sharing across every workspace and compute type, and as of 2026 extends the same governance model to AI assets such as models, functions, and connections. A useful mental model is "secure by default": querying an object typically requires both container privileges (USE CATALOG + USE SCHEMA) and an object privilege (like SELECT), while governance objects (storage credentials, external locations) gate all cloud storage access. Since September 30 2025, Unity Catalog is mandatory for all new workspaces.

What This Cheat Sheet Covers

This topic spans 18 focused tables and 172 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Core Namespace ObjectsTable 2: Metastore Setup & OperationsTable 3: Catalog & Schema DDLTable 4: Table & View DDLTable 5: Table Types & ConversionTable 6: Volumes (Non-tabular Data)Table 7: Cloud Storage Governance ObjectsTable 8: Privilege Model ConceptsTable 9: Grants & Core PrivilegesTable 10: Tags, Governed Tags & ABACTable 11: Row Filters & Column MasksTable 12: Metadata Discovery (Information Schema)Table 13: Audit, Lineage & System TablesTable 14: Sharing & Clean RoomsTable 15: Federation, Connections & Foreign CatalogsTable 16: Data Classification & AI GovernanceTable 17: Data Optimization & MaintenanceTable 18: Automation (REST API, CLI, IaC)

Table 1: Core Namespace Objects

ObjectExampleDescription
Metastore
metastore → catalogs → schemas → objects
• Top-level container for Unity Catalog metadata and permissions
• one per region per account.
Catalog
sales_catalog.analytics.orders
• First namespace level that groups schemas
• maps to environments, domains, or teams.
Schema
sales_catalog.analytics
Second namespace level (also called database) that groups tables, views, functions, volumes, and models.
Table
SELECT * FROM sales_catalog.analytics.orders;
• Structured dataset registered in a schema
• can be managed, external, or foreign.
View
SELECT * FROM sales_catalog.analytics.active_customers;
Read-only named query that executes at read time.
Materialized View
SELECT * FROM sales_catalog.analytics.daily_revenue;
Precomputed view whose results are stored and refreshed incrementally.

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