Verified project record

apache/airflow

Apache Airflow is a platform for authoring, scheduling, and monitoring workflows as code. It targets data teams that need to orchestrate tasks and data pipelines, but does not provide native Windows support or handle streaming workloads.

Project overview

Project type: Workflow · Data Processing · Infrastructure
Use cases: Documents & Office
Deployment: Refer to project documentation
License: Apache-2.0

Best for

Data teams and operations teams needing to author, schedule, and monitor workflows as code.

Key capabilities

Enables users to author workflows (DAGs) as code that orchestrate tasks, making them maintainable, versionable, testable, and collaborative.
Executes scheduled tasks on an array of workers while following specified dependencies.
A rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues.
Provides command line utilities to perform complex surgeries on DAGs.
Leverages the Jinja templating engine allowing rich customizations and dynamic DAG generation.
Includes a wide range of built-in operators and can be extended to fit user needs via providers.

Limitations and risks

There is no native Windows support; users must use WSL2 or Linux Containers.
The platform is not a streaming solution and is not suitable for streaming workloads.
Pip installation can fail or produce unusable installations without constraint files due to open dependencies.

Getting started

Setup difficulty is medium; installation requires managing dependencies and constraints using Python pip constraint files to avoid failures, and requires setting up a scheduler and workers.

Evidence and sources

README: Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows.
README: When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative.
README: The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.
README: We know about around 500 organizations that are using Apache Airflow (but there are likely many more)
README: Apache Airflow version life cycle:

Reviewed at: 2026-07-17T07:21:56Z