Databricks

About Databricks

Databricks provides reference documentation for its platform's developer-facing interfaces, including REST APIs (Databricks REST API, MLflow REST API, Account SCIM v2.1 API, Jobs v2.0 API), language-specific APIs for Python, Scala, and SQL, and developer tools such as the Databricks CLI, Terraform provider, and SDKs for Python, R, Java, and Go.

The documentation covers data and AI/ML functionality including PySpark, Delta Lake, Lakeflow pipelines, AutoML, MLflow, AI Search, feature engineering and feature store operations, agent evaluation and deployment, and integrations with LangChain, OpenAI SDK, and MCP servers. It also includes SQL error codes and error class references for troubleshooting.

This resource is intended for developers and data engineers building on Databricks, covering data processing, machine learning workflows, generative AI application monitoring, and automation across multiple programming languages and deployment tools.

Key features

• REST API reference covering Databricks services, MLflow, SCIM, and Jobs
• PySpark, Scala Spark, and Delta Lake API references
• SDKs for Python, R, Java, and Go
• Databricks CLI and Terraform provider for automation and infrastructure management
• Python APIs for AI/ML workflows including AutoML, MLflow, AI Search, and agent evaluation
• Databricks SQL reference including syntax, functions, and operators

Frequently asked questions