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DP-750 · 1.2.5 · Set up and configure an Azure Databricks environment

Tables and views

Create tables, views, and materialized views

Choose persisted tables, logical views, or materialized views based on storage and freshness requirements.

Pick by what should persist

  • Table

    Stores rows
    Yes
    Stores query logic
    Sometimes
    Recomputes on read
    No

  • View

    Stores rows
    No
    Stores query logic
    Yes
    Recomputes on read
    Yes

  • Materialized view

    Stores rows
    Yes
    Stores query logic
    Yes
    Recomputes on read
    No
Table, view, or materialized view

A table stores rows. A standard view stores query logic and computes on read. A materialized view stores refreshed results from its defining query.

See how materialization works

Microsoft Learn diagram showing source data flowing through a managed flow into a materialized view.

Materialized views are maintained through a managed flow. They fit repeated expensive transformations when precomputed results and managed refresh behavior meet the freshness requirement.

Place the object correctly

Microsoft Learn Unity Catalog object model showing the metastore, catalogs, schemas, tables, views, volumes, functions, models, and services.

Tables and views both live at the object level inside a schema. Choose the object type from persistence and refresh semantics, not from how tabular the result looks.

Key points

  • Table: Persists data rows
  • View: Stores query logic and computes on read
  • Materialized view: Stores refreshed query results
  • Security: Views can provide governed logical interfaces

Exam trap

A normal view does not precompute and persist its query result.

Sources · 2 Microsoft Learn pages Show ▾

Checked on October 4, 2026. Report a problem

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