How can I use Visual Studio Code with Azure Databricks?
Visual Studio Code by Microsoft is a lightweight but powerful source code editor which runs on your desktop and is available for Windows, macOS, and Linux. It comes with built-in support for JavaScript, TypeScript and Node.js and has a rich ecosystem of extensions for other languages and runtimes (such as C++, C#, Java, Python, PHP, Go, and .NET). Visual Studio Code combines the simplicity of a source code editor with powerful developer tooling, like IntelliSense code completion and debugging. You can use Visual Studio Code on your local development machine to write, run, and debug code in Azure Databricks, interact with Databricks SQL warehouses in remote Azure Databricks workspaces, and more, as follows:
| Name | Use this when you want to… |
|---|---|
| Databricks extension for Visual Studio Code | Use Visual Studio Code to write and run local Python, R, Scala, and SQL code on a remote Azure Databricks workspace. |
| Databricks Connect in Visual Studio Code with Python | Use Visual Studio Code to write, run, and debug local Python code on a remote Azure Databricks workspace. |
| Databricks Connect in Visual Studio Code with Scala | Use Visual Studio Code to write, run, and debug local Scala code on a remote Azure Databricks workspace. |
| Databricks Asset Bundles | Use Visual Studio Code to make authoring, deploying, and running bundles easier. Databricks Asset Bundles (or bundles for short) enable you to programmatically define, deploy, and run Azure Databricks jobs, Delta Live Tables pipelines, and MLOps Stacks by using CI/CD best practices and workflows. |
| Databricks CLI | Use the built-in Terminal in Visual Studio Code to work with Azure Databricks from the command line. |
| Databricks SDKs | Use the built-in programming language support in Visual Studio Code to write, run, and debug Python, Java, and Go code that works with Azure Databricks. |
| Databricks Driver for SQLTools | Use a graphical user interface in Visual Studio Code to query Databricks SQL warehouses in remote Azure Databricks workspaces. |
| Databricks SQL connectors, drivers, and APIs | Use the built-in programming language support in Visual Studio Code to write, run, and debug Python, Go, JavaScript, TypeScript, and Node.js code that works with Databricks SQL warehouses in remote Azure Databricks workspaces. |
| Provision infrastructure | Use third-party plugins such as the Hashicorp Terraform Extension for Visual Studio Code to make it easier to provision Azure Databricks infrastructure with Terraform and follow infrastructure-as-code (IaC) best practices. Use the built-in programming language support in Visual Studio Code to write and deploy Python, TypeScript, Java, C#, and Go definitions of Azure Databricks infrastructure through third-party offerings such as the Cloud Development Kit for Terraform (CDKTF) and Pulumi. |