Databricks
Manage Databricks accounts, clusters, notebooks, jobs, and workspaces via API.
Read docs Updated 2026-06-17
What is Databricks?
The Databricks API is a management interface for Databricks accounts, clusters, notebooks, jobs, and workspaces.
It is useful for developers and teams automating infrastructure, job scheduling, and workspace administration in data platform environments.
What you can build with Databricks
Automate cluster lifecycle management
Programmatically create, start, resize, and terminate Spark clusters based on workload demands or schedules.
Orchestrate data pipelines via jobs
Create, trigger, and monitor jobs that run notebooks or JARs as part of automated ETL or ML workflows.
Manage collaborative workspaces
Organize, version, and share notebooks and folders across teams using workspace and notebook APIs.
Get started with Databricks
- 1Create a Databricks account and generate an API access token
- 2Review the REST API reference documentation for endpoints
- 3Send HTTPS requests using the token in the Authorization header
- 4Test basic calls such as listing clusters or jobs
- 5Integrate calls into scripts or CI/CD automation
Databricks: pros & cons
Pros
- +Full programmatic control over clusters, jobs, and workspaces
- +Secure API key authentication over HTTPS
- +Enables reliable automation of data and ML workflows
- +Broad coverage of accounts, notebooks, and workspace resources
Cons
- –Requires an active Databricks subscription
- –API surface can be extensive to learn
- –Usage subject to platform rate limits and quotas
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Frequently asked questions
It is a REST API that lets developers control Databricks resources such as clusters, jobs, notebooks, and workspaces using API key authentication.
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