SQL connectors, libraries, drivers, APIs, and tools
Databricks has SQL connectors, libraries, drivers, APIs, and tools that allow you to connect to 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: |
---|---|
Run SQL commands directly from Python code. This connector is easier to set up than other Python libraries, such as pyODBC. |
|
Use Python to interact with 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. |
|
Authenticate and establish a connection from your local Python code to Databricks using ODBC. |
|
Integrate Go applications with Databricks and use familiar SQL interfaces in the Go programming environment. |
|
Use JavaScript or TypeScript when building applications to query and manipulate data stored in Databricks. |
|
Connect participating apps, tools, clients, SDKs, and APIs to Databricks through Open Database Connectivity (ODBC), an industry-standard specification for accessing database management systems. |
|
Connect participating apps, tools, clients, SDKs, and APIs to Databricks through Java Database Connectivity (JDBC), an industry-standard specification for accessing database management systems. |
|
Run SQL statements to access Databricks data and retrieve results without the need to install database drivers or manage persistent connections. |
|
Run SQL commands and scripts from the command line. The Databricks SQL CLI connects to Databricks and allows for integration into scripts and automation processes. |
|
Run SQL queries directly against Databricks from within Visual Studio Code. |
|
Use DataGrip’s integrated development environment (IDE) to connect to 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. |
|
Integrate DBeaver, a multi-platform database tool that uses the JDBC protocol, to view and manage data in Databricks. Use the DBeaver SQL editor, data and schema migration tools, and database connection monitoring capabilities. |
|
Use SQL Workbench/J, a Java-based tool, for connecting to data in Databricks and running SQL scripts without being constrained by operating system limitations. |