Azure Databricks for SQL developers

This section provides a guide to developing notebooks in the Databricks Data Science & Engineering and Databricks Machine Learning environments using the SQL language.

Databricks SQL

If you are a data analyst who works primarily with SQL queries and BI tools, Databricks SQL provides an intuitive environment for running ad-hoc queries and creating dashboards on data stored in your data lake. You may want to skip this article, which is focused on developing notebooks in the Databricks Data Science & Engineering and Databricks Machine Learning environments. Instead see:

SQL Reference

The SQL language reference that you use depends on the Databricks Runtime version that your cluster is running:

For Databricks SQL, see SQL reference for Databricks SQL.

Use cases

Visualizations

SQL notebooks support various types of visualizations using the display function.

Interoperability

This section describes features that support interoperability between SQL and other languages supported in Azure Databricks.

Tools

In addition to Azure Databricks notebooks, you can also use various third-party developer tools, data sources, and other integrations. See Databricks integrations.

Access control

This article describes how to use SQL constructs to control access to database objects:

Resources