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apache-airflow-providers-mongo

Provider package apache-airflow-providers-mongo for Apache Airflow

apache-airflow-providers-mongo v5.4.0 1.6M downloads/30d#3,685 on PyPI46,490
Permissive license Apache-2.0 Active released

What it is and what it does

This is an Apache Airflow provider package that extends Airflow's orchestration capabilities to work with MongoDB. It supplies operators, hooks, and connection types that allow DAG tasks to authenticate to MongoDB instances, execute queries, and manage data workflows. The package depends on pymongo for the actual MongoDB client library and dnspython for DNS resolution, and integrates with Airflow's connection and credential management system.

You install it on top of an existing Airflow deployment to add MongoDB-specific task types to your DAGs. It is maintained as part of the Apache Airflow project and supports current Python versions (3.10 through 3.14). The package is production-stable and actively maintained, with no known security vulnerabilities.

Use it for:

  • Extract data from MongoDB collections as part of a scheduled ETL pipeline in Airflow
  • Load transformed data into MongoDB from upstream tasks or external sources
  • Query MongoDB for validation or monitoring checks within a DAG workflow
  • Manage MongoDB operations (index creation, collection cleanup) as orchestrated tasks
  • Integrate MongoDB data sources with multi-step Airflow data pipelines

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Integrates MongoDB with Apache Airflow as a provider package, enabling DAG tasks to connect to, query, and manage MongoDB databases.

Yes. Install this if you run Apache Airflow and need to orchestrate MongoDB operations. Low install friction, active maintenance, no vulnerabilities, and permissive licensing make it a straightforward addition to an Airflow environment. Requires Airflow >=2.11.0 and Python >=3.10.

Install

apache-airflow-providers-mongo on PyPI

pip

pip install apache-airflow-providers-mongo

uv

uv add apache-airflow-providers-mongo

poetry

poetry add apache-airflow-providers-mongo

Installing apache-airflow-providers-mongo

Before you install

Low friction installation as a wheel. Active maintenance with recent release (83 days old) and no known vulnerabilities. Requires Apache Airflow >=2.11.0 and modern Python (3.10+).

License in practice

Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most organizational contexts.

Quickstart

pip install apache-airflow-providers-mongo

from airflow.providers.mongo.operators.mongo import MongoOperator
from airflow import DAG

with DAG('mongo_example') as dag:
    task = MongoOperator(mongo_conn_id='mongo_default', task_id='query_mongo')

Requires Apache Airflow >=2.11.0 and Python >=3.10; MongoDB server must be accessible via configured connection.

Verify before relying

  • Specific operators and hooks available beyond what the description excerpt states
  • Whether the package supports MongoDB Atlas or only self-hosted instances
  • Performance characteristics for large-scale data transfers

Package facts

License Apache-2.0 (permissive)
Python support supports the current Python release (>=3.10)
Install friction low — pure-Python wheel
Runtime dependencies 4 — apache-airflow, apache-airflow-providers-common-compat, dnspython, pymongo
Maintenance actively maintained — 83 days since the last release
Last repo commit
First released
Downloads 1,648,888/month — #3,685 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: apache_airflow_providers_mongo-5.4.0-py3-none-any.whl

Keywords: airflow-provider, mongo, airflow, integration

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

Tags

airflow mongodb integrationairflow mongo providermongodb airflow tasksairflow database operatorsmongo connection airflowairflow data pipeline mongodbmongodb airflow dag
airflow-providermongodb-integrationdata-orchestration

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