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SQL connectors, libraries, drivers, APIs, and tools

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Azure Databricks has SQL connectors, libraries, drivers, APIs, and tools that allow you to connect to Azure Databricks, interact programmatically, and integrate Databricks SQL functionality into applications written in popular languages such as Python, Go, JavaScript and TypeScript.

Name Allows you to:
SQL connnector to Python Run SQL commands directly from Python code. This connector is easier to set up than other Python libraries, such as pyODBC.
SQLAlchemy Use Python to interact with Azure Databricks as a SQL data source. SQLAlchemy is a Python SQL toolkit that allows you to work with Python objects instead of writing raw SQL queries.
[Python and pyODBC](pyodbc. md) Authenticate and establish a connection from your local Python code to Azure Databricks using ODBC.
Databricks SQL Driver for Go Integrate Go applications with Azure Databricks and use familiar SQL interfaces in the Go programming environment.
Databricks SQL Driver for Node.js Use JavaScript or TypeScript when building applications to query and manipulate data stored in Azure Databricks.
Databricks ODBC Driver Connect participating apps, tools, clients, SDKs, and APIs to Azure Databricks through Open Database Connectivity (ODBC), an industry-standard specification for accessing database management systems.
Databricks JDBC Driver and Databricks JDBC Driver (OSS) Connect participating apps, tools, clients, SDKs, and APIs to Databricks through Java Database Connectivity (JDBC), an industry-standard specification for accessing database management systems.
Databricks SQL Statement Execution API Run SQL statements to access Azure Databricks data and retrieve results without the need to install database drivers or manage persistent connections.
Databricks SQL CLI Run SQL commands and scripts from the command line. The Databricks SQL CLI connects to Azure Databricks and allows for integration into scripts and automation processes.
Databricks Driver for SQLTools for Visual Studio Code Run SQL queries directly against Azure Databricks from within Visual Studio Code.
DataGrip integration with Azure Databricks Use DataGrip’s integrated development environment (IDE) to connect to Azure Databricks for application development, providing a query console, schema navigation, plan explanation, smart code completion, real-time analysis and quick fixes, refactorings, version control integration, and other features.
DBeaver integration with Azure Databricks Integrate DBeaver, a multi-platform database tool that uses the JDBC protocol, to view and manage data in Azure Databricks. Use the DBeaver SQL editor, data and schema migration tools, and database connection monitoring capabilities.
Connect to SQL Workbench/J Use SQL Workbench/J, a Java-based tool, for connecting to data in Azure Databricks and running SQL scripts without being constrained by operating system limitations.