apache-airflow-providers-microsoft-azure
Provider package apache-airflow-providers-microsoft-azure for Apache Airflow
Decision gist · record as of 2026-08-14
Yes, if you run Apache Airflow and need to orchestrate Azure workloads. The package is production-stable, actively maintained, and permissively licensed. The 33 dependencies are substantial but expected for comprehensive Azure SDK coverage. Verify that your Airflow deployment meets the >=2.11.0 requirement and that your environment can accommodate the Azure SDK footprint; no known vulnerabilities as of the query date.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Apache Airflow >=2.11.0 and Python 3.10 or later; Azure credentials and connectivity to Azure services must be configured outside the package.
- Low friction installation with a pure-Python wheel.
- Actively maintained—released 6 days ago with 46490 repository stars.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing use in commercial and proprietary projects with minimal restrictions; include a copy of the license and note any material modifications.
last release 2026-08-08 (6 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,092,574 downloads/mo, #3,302 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-microsoft-azure
from airflow.providers.microsoft.azure.operators.adls import ADLSDeleteOperator
from airflow.models import DAG
with DAG('azure_example') as dag:
delete_task = ADLSDeleteOperator(task_id='delete_adls', path='/data')- Specific operators, sensors, and hooks available in version 14.1.0 beyond the Azure SDK services listed.
- Whether all 33 dependencies are always required or if some are optional for specific Azure services.
- Performance characteristics and scalability limits for large-scale Azure resource orchestration.
What it is and what it does
This is an Apache Airflow provider package that bridges Airflow's workflow orchestration engine to Microsoft Azure's cloud services. It exposes Azure resources—storage accounts, data lakes, Cosmos DB, Synapse, Batch, Container Instances, and more—as Airflow operators, hooks, and sensors, allowing you to define, schedule, and monitor Azure-based data pipelines and infrastructure tasks as DAGs.
The package wraps the official Azure SDK libraries (33 runtime dependencies covering storage, compute, identity, and data services) and integrates them into Airflow's task execution model. You install it on top of an existing Airflow deployment, define tasks using Azure operators, and Airflow handles scheduling, retry logic, and monitoring. It supports Python 3.10 through 3.14 and is actively maintained by the Apache Airflow project.
Use it for
- Schedule and monitor Azure Data Lake or Blob Storage data ingestion and transformation jobs within Airflow DAGs.
- Orchestrate Azure Synapse Spark jobs, Batch compute tasks, or Container Instance deployments as part of multi-step workflows.
- Automate Azure resource provisioning, scaling, and lifecycle management (compute, storage, container registry) via Airflow.
- Build hybrid cloud pipelines that coordinate Azure services with AWS, GCP, or on-premises systems using Airflow's cross-provider support.
- Manage secrets and authentication to Azure services through Azure Key Vault integration within Airflow task execution.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you run Apache Airflow and need to orchestrate Azure workloads.
The package is production-stable, actively maintained, and permissively licensed. The 33 dependencies are substantial but expected for comprehensive Azure SDK coverage. Verify that your Airflow deployment meets the >=2.11.0 requirement and that your environment can accommodate the Azure SDK footprint; no known vulnerabilities as of the query date.
Install
apache-airflow-providers-microsoft-azure on PyPI
Before you install
Low friction installation with a pure-Python wheel. Actively maintained—released 6 days ago with 46490 repository stars. Requires Apache Airflow >=2.11.0 and pulls in 33 runtime dependencies, all Azure SDK packages; evaluate whether your environment can accommodate this dependency footprint.
Requires Apache Airflow >=2.11.0 and Python 3.10 or later; Azure credentials and connectivity to Azure services must be configured outside the package.
License in practice
Licensed under Apache-2.0 (permissive), allowing use in commercial and proprietary projects with minimal restrictions; include a copy of the license and note any material modifications.
Quickstart
pip install apache-airflow-providers-microsoft-azure
from airflow.providers.microsoft.azure.operators.adls import ADLSDeleteOperator
from airflow.models import DAG
with DAG('azure_example') as dag:
delete_task = ADLSDeleteOperator(task_id='delete_adls', path='/data')Verify before relying
- Specific operators, sensors, and hooks available in version 14.1.0 beyond the Azure SDK services listed.
- Whether all 33 dependencies are always required or if some are optional for specific Azure services.
- Performance characteristics and scalability limits for large-scale Azure resource orchestration.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 33 packagesapache-airflowapache-airflow-providers-common-compatadlfsaiohttpazure-batchazure-ai-projectsazure-cosmosazure-mgmt-cosmosdbazure-datalake-storeazure-identityazure-keyvault-secretsazure-mgmt-datalake-storeazure-mgmt-resourceazure-storage-blobazure-mgmt-storageazure-storage-file-shareazure-servicebusazure-synapse-sparkazure-synapse-artifactsazure-storage-file-datalakeazure-kusto-dataazure-mgmt-datafactoryazure-mgmt-containerregistryazure-mgmt-computeazure-mgmt-containerinstancemsgraph-coremsgraphfsmicrosoft-kiota-httpmicrosoft-kiota-serialization-jsonmicrosoft-kiota-serialization-text |
| Maintenance | Actively maintained 6 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,092,574 / month, #3,302 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: Web EnvironmentFramework :: Apache AirflowFramework :: Apache Airflow :: ProviderIntended Audience :: DevelopersIntended Audience :: System AdministratorsProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: System :: Monitoring |
Evidence: apache_airflow_providers_microsoft_azure-14.1.0-py3-none-any.whl
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See also apache-airflow-providers-google · apache-airflow-providers-oracle · apache-airflow-providers-snowflake · apache-airflow-providers-databricks · apache-airflow-providers-microsoft-mssql · apache-airflow-providers-apache-kafka · apache-airflow-providers-amazon · apache-airflow-providers-sftp · apache-airflow-providers-standard · apache-airflow-providers-common-messaging