What is Apache Airflow?
Apache Airflow is an open-source platform for defining, scheduling and monitoring workflows in Python. Its tasks and dependencies coordinate bounded pipeline work, including jobs executed by other systems. The orchestrator does not supply a warehouse or make every task safe to repeat.
Who is Apache Airflow for?
Engineering teams maintaining coded workflows across data services and other systems.
Apache Airflow features
The core capabilities to consider for your workflow.
- Python-defined workflows and dependencies
- Scheduling, retries and historical runs
- Task logs and workflow monitoring
- Extensible operators and providers
Apache Airflow pricing
Free self-managed orchestrator
Budget for the control plane, execution infrastructure, logs and operator time. Jobs submitted to other services retain their own usage charges.
Calculate the cost of your quote →Free access & evaluation
The upstream software is free to self-manage. Infrastructure, operators and third-party managed Airflow services have separate costs.
Before you choose Apache Airflow
Operate the scheduler, metadata database, workers and upgrades, or choose a separate managed service.
Continuous event transport and large data processing need the appropriate additional systems.
Explore Apache Airflow in more detail
Take a closer look at the decisions behind this product.
Airflow vs Azure Data Factory: orchestration and runtime ownership
Read the articleCompare Apache Airflow
Explore the individual profiles
Apache Airflow FAQs
Does Apache Airflow have a free plan?
The upstream software is free to self-manage. Infrastructure, operators and third-party managed Airflow services have separate costs.
Who is Apache Airflow for?
Engineering teams maintaining coded workflows across data services and other systems.
What should I compare before buying?
Check the tier that contains your essential features, confirm plan limits and compare the total quote with your own expected usage.