Azure Databricks tables

Azure Databricks provides multiple table types and storage formats to meet different data management needs. This section covers managed, external, and foreign tables, along with the Delta Lake and Apache Iceberg storage formats that power advanced features like Atomicity, Consistency, Isolation, and Durability (ACID) transactions and time travel.

Core concepts

Learn the fundamentals of table types, storage formats, and Unity Catalog integration.

Topic Description
Tables concepts Core concepts and foundational information about table types, storage formats, and Unity Catalog integration.

Table types

Explore different table types and their capabilities for various data management scenarios.

Table type Description
Managed tables Tables where Azure Databricks manages both metadata and data files. Recommended for new tables with optimized performance and storage.
External tables Tables that reference data stored in external storage systems while managing metadata in Unity Catalog.
Foreign tables Read-only tables representing data in external systems connected through Lakehouse Federation.

Storage formats

Work with open table formats that provide advanced data management capabilities.

Format Description
Delta Lake Default storage format providing ACID transactions, time travel, and schema enforcement for managed and external tables.
Apache Iceberg Open table format for integration with the Iceberg ecosystem, supporting advanced metadata management.

Table management

Configure and optimize table behavior, structure, and performance.

Feature Description
Table constraints Define and enforce data quality rules with check constraints and not null constraints.
Schema enforcement Control how Azure Databricks handles schema changes and data type enforcement during writes.
Table partitioning Organize data by partition keys to improve query performance and data management.
Table size monitoring Monitor and analyze table storage usage and growth patterns.
External partition discovery Automatically discover and register partitions in external tables stored in cloud storage.