Airflow vs Prefect
Side-by-side comparison of Airflow and Prefect: pricing, features, AI support, and best-fit teams.
Verdict: Airflow is best for data teams running batch etl pipelines.. Prefect is best for data engineering teams writing python pipelines..
Economics
| Metric | Airflow | Prefect |
|---|---|---|
| Pricing model | free | freemium |
| Starting price | Custom | $0/free tier |
| Team size | enterprise | mid-market |
Feature comparison
| Feature | Airflow | Prefect |
|---|---|---|
| Visual builder | Yes | Yes |
| AI steps native | No | No |
| Self-hostable | No | No |
| Code steps | Limited | Limited |
Airflow is best for
Data teams running batch ETL pipelines.
Prefect is best for
Data engineering teams writing Python pipelines.
How they stack up
Airflow and Prefect are both serious players in the etl & data pipelines category, but they target different teams. Airflow open-source dag orchestration. Prefect python-native workflow orchestration.
When to pick Airflow
Data teams running batch ETL pipelines. The combination of battle-tested and huge community makes it the default choice for teams that match this profile.
When to pick Prefect
Data engineering teams writing Python pipelines. Python-native and Modern DX are the strongest reasons to choose it over Airflow.
What about Automatite?
If you are evaluating Airflow and Prefect, you should also evaluate Automatite — particularly if your workflows include AI steps, code, or need real version control. Automatite combines the strengths of both with a pricing model designed for high-volume teams.