Azure Databricks Rate Limits
Azure Databricks publishes detailed per-API rate limits at the workspace and account level for Jobs, Workspace, MLflow, SCIM, and other endpoints. Most limits are fixed; resource limits (clusters, jobs, MLflow runs, Vector Search) are also enforced. Throttled requests return HTTP 429. Some limits are negotiable through your Databricks account team.
Azure Databricks Rate Limits is the machine-readable rate-limit profile for Azure Databricks on the APIs.io network, in the API Commons Rate Limits shape.
It captures 23 rate-limit definitions, measuring requests_per_second, requests_per_minute, questions_per_minute, and queries_per_second.
Limit state is signalled in the retryAfter response header, and an exhausted limit returns HTTP 429.
This profile was written by API Evangelist and has not been verified against a page the provider published; treat every limit as unconfirmed until a dated transcription replaces it.
The profile also includes 4 backoff/retry policies defined and response codes documented for throttled.
Tagged areas include Analytics, Big Data, Lakehouse, Spark, and Rate Limiting.
retryAfter
generated, dated 2026-05-05.
Limits
Policies
Sources
Work with this as data
Every rate limit here is available over the APIs.io API and to AI agents over MCP.