Apache Airflow

Open-source, Python-native workflow platform behind most modern data pipelines

Deployment Cloud Based, On Premises
Starting price Free
Free trial Not offered
Best for Freelancers, SMEs, Enterprises

What is Apache Airflow?

Apache Airflow is a platform created by its community to programmatically author, schedule and monitor workflows, and it has become the default choice for data-engineering pipeline orchestration specifically, distinct from the IT-operations focus of most other tools in this category. Pipelines are defined as Python code rather than through a GUI or proprietary job language, which is precisely why data teams gravitated toward it.

Its four stated principles are scalable (a modular, message-queue-based architecture that scales to an arbitrary number of workers), dynamic (pipelines defined in Python enabling dynamic generation), extensible (custom operators and extended libraries), and elegant (lean, explicit pipelines using Jinja templating). Airflow is free and open source, maintained by the Apache community, with an annual Airflow Summit. Several vendors in this category, including Broadcom's Automic, explicitly build integration layers for Airflow rather than treating it as a competitor to route around.

Key Features of Apache Airflow

Author workflows as Python code
Schedule and monitor pipelines centrally
Scale to an arbitrary number of workers
Generate pipelines dynamically at runtime
Extend with custom operators and libraries
Write lean, explicit pipeline definitions
Use Jinja templating for parameterisation
Run entirely as free, open-source software
Integrate with major cloud data platforms
Join a large open-source contributor community

Apache Airflow Pricing

Open source

Free

Free, community-maintained

Free Trial

Apache Airflow is entirely free and open source. Managed hosting is available from several third-party cloud providers at their own published rates, separate from the project itself.

Apache Airflow Specifications

Software Tagline :

Open-source, Python-native workflow platform behind most modern data pipelines

Deployment :

cloud based
on premises

Subscription Plan :

monthly

Desktop Platforms :

web app

Mobile Platforms :

Language Support :

Target Audience :

freelancers
smes
enterprises

Available Support :

email
tickets

Integrations :

Cloud data platforms, Python libraries, major data warehouses

Product Url :

https://airflow.apache.org/

API Available :

Yes

Free Trial Available :

Run On Mobile Browser :

Yes

Free Plan Available :

Yes

Customization Available :

Yes

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Apache Airflow FAQs

Airflow is an open-source platform for programmatically authoring, scheduling and monitoring workflows, widely used for data-engineering pipelines.

It is Python-native and built around data pipeline orchestration, which is why data engineering teams use it rather than the IT-operations-focused tools elsewhere in this category.

Yes, it is free and open source, maintained by the Apache community. Managed hosting from cloud providers is priced separately.

Several, including Broadcom's Automic, build integration layers specifically for Airflow rather than positioning against it, since it is often already embedded in data teams' workflows.

Scalable, dynamic, extensible and elegant, reflecting its modular architecture, Python-based pipeline definition, custom operator support and lean syntax.