· Data Engineering · 2 min read
Airflow vs Prefect: Choosing the Right Orchestrator for 2025
The battle of the Python orchestrators. We compare the industry standard (Airflow) against the modern challenger (Prefect).
Every data platform needs a conductor to wave the baton and tell the instruments when to play. For years, Apache Airflow has been the undisputed king. But newer tools like Prefect (and Dagster) are challenging the throne. Which one should you pick?
Apache Airflow: The Heavyweight
- Pros: Huge community, integrates with absolutely everything (AWS, GCP, Snowflake), proven at massive scale.
- Cons: Can be complex to set up (needs a Scheduler, Webserver, Worker, Database), handling “dynamic” workflows is clunky, and the developer experience can feel a bit dated.
- Verdict: Best for large enterprise teams who need a standard, battle-tested solution.
Prefect: The Modern challenger
- Pros: purely pythonic (you just decorate your functions with
@task), handles dynamic mapping beautifully, excellent UI, hybrid execution model (keepers your code private while using their cloud for orchestration). - Cons: Smaller community, fewer “out of the box” operators compared to Airflow.
- Verdict: Best for modern data teams who want a great developer experience and need to handle complex, dynamic logic.
It Depends on Your Team
If you have a team of strong Python developers, they will likely prefer Prefect. If you have a team of traditional Data Engineers who want a stable ecosystem, Airflow is the safer bet.
Need help architecting your platform? We have deployed both at scale. Get an unbiased recommendation.
