Developer tools and guidance
Learn about tools and guidance you can use to work with Azure Databricks resources and data and to develop Azure Databricks applications.
|Section||Use this section when you want to…|
|Authentication||Authenticate with Azure Databricks from your tools, scripts, and apps. You must authenticate with Azure Databricks before you can work with Azure Databricks resources and data.|
|IDEs||Connect to Azure Databricks by using popular integrated development environments (IDEs) such as Visual Studio Code, PyCharm, IntelliJ IDEA, Eclipse, and RStudio, as well as automate Azure Databricks by using IDE plugins.|
|SDKs||Automate Azure Databricks from code libraries written for popular languages such as Go.|
|CLIs||Automate Azure Databricks by using command-line interfaces (CLIs).|
|Utilities||Use Databricks Utilities from within notebooks to do things such as work with object storage efficiently, chain and parameterize notebooks, and work with sensitive credential information.|
|REST API (latest)||Call Azure Databricks automation APIs directly by using popular clients such as
|Python API||Call Azure Databricks automation APIs directly with Python by using the Databricks CLI package as a Python library.|
|IaC||Automate the provision and maintenance of Azure Databricks infrastructure and resources by using popular infrastructure-as-code (IaC) products such as Terraform, the Cloud Development Kit for Terraform, and Pulumi.|
|CI/CD||Implement industry-standard continuous integration and continuous delivery (CI/CD) practices for Azure Databricks by using popular systems such as GitHub Actions, Azure Pipelines, GitLab CI/CD, Jenkins, and Apache Airflow.|
|SQL tools||Run SQL commands and scripts in Azure Databricks by using Databricks CLIs, as well as popular tools such as DataGrip, DBeaver, and SQL Workbench/J.|
|Service principals||Use identities called service principals as a security best practice to authenticate automated scripts, tools, apps, and systems with Azure Databricks.|
You can also connect many additional popular third-party tools to clusters and SQL warehouses to access data in Azure Databricks. See the Databricks integrations.