---
id: azure-mgmt-databricks
version: "3.0.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# azure-mgmt-databricks — Microsoft Azure Databricks Management Client Library for Python

License: permissive · Maintenance: active · Downloads: 661.6K/mo

## What it is and what it does

This is the official Azure SDK client library for managing Databricks resources in Azure. It wraps the Azure Resource Manager API to let you programmatically create, configure, and delete Databricks workspaces, clusters, access connectors, and related infrastructure. The library depends on isodate, azure-mgmt-core, and typing-extensions to handle REST communication, authentication, and type hints.

Version 3.0.0 introduces hybrid models with dual dictionary and model behavior, adds cloud_setting configuration, and expands the API surface with new resource types like AutomaticClusterUpdateDefinition and EnhancedSecurityComplianceDefinition. It requires Python 3.10 or later and authenticates via Microsoft Entra using environment variables or credential objects.

Use it for:

- Automate provisioning and teardown of Databricks workspaces as part of infrastructure-as-code pipelines.
- Manage workspace access connectors and private endpoint connections for network isolation.
- Configure workspace security settings, encryption, and compliance profiles programmatically.
- Integrate Databricks resource management into Python-based DevOps or cloud orchestration tools.
- Query and monitor workspace properties, provisioning state, and system metadata.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides Python bindings to manage Azure Databricks workspaces, clusters, and related resources through the Azure Resource Manager API.

Yes. This is the official, actively maintained Azure SDK for Databricks management with no known vulnerabilities, low install friction, and permissive licensing. Install it if you need to manage Azure Databricks resources from Python code. Be aware that version 3.0.0 introduces breaking changes to model structures that may require migration if upgrading from earlier versions.

## Install

pip install azure-mgmt-databricks
uv add azure-mgmt-databricks
poetry add azure-mgmt-databricks

## Installing azure-mgmt-databricks

Before you install: Low install friction with a pure-Python wheel distribution. Actively maintained with recent release (37 days old) and no known vulnerabilities. Requires Python 3.10 or later.

License in practice: MIT license permits commercial and private use with minimal restrictions; suitable for most deployment scenarios.

Quickstart:

pip install azure-mgmt-databricks

from azure.mgmt.databricks import AzureDatabricksManagementClient
from azure.identity import DefaultAzureCredential
import os

sub_id = os.getenv("AZURE_SUBSCRIPTION_ID")
client = AzureDatabricksManagementClient(
    credential=DefaultAzureCredential(),
    subscription_id=sub_id
)

Requires Azure subscription and environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET, and AZURE_SUBSCRIPTION_ID for authentication.

Verify before relying:

- Whether version 3.0.0's breaking changes to hybrid models require significant refactoring for existing codebases.
- Performance characteristics and rate limits when managing large numbers of workspaces or clusters.
- Compatibility with non-Azure cloud environments or hybrid deployments.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 661.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

azure databricks management, azure resource manager python, databricks workspace provisioning, azure sdk databricks, manage databricks clusters, azure infrastructure as code, azure-sdk, infrastructure-as-code, cloud-management

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