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Automation Integration · head to head

Prefect vs Apache Airflow

Prefect logo

Prefect

Automation Integration

Python-first workflow orchestration that heals itself

From
Free
Rated
-
Full reviewWebsite
Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Prefect limited to Python-based workflows; other languages require API calls; Apache Airflow self-hosting is genuinely heavy: scheduler, metadata database, workers and executor choice are a standing operational job
  • They diverge on capability: Prefect covers Python function decorators, Apache Airflow covers Pipelines as Python.

Where they differ

Only the attributes on which Prefect and Apache Airflow actually diverge.

Attributes where Prefect and Apache Airflow differ
AttributePrefectApache Airflow
Pricing modelFreemium with per-user and usage-based tiersOpen source, no licence fee; managed services billed separately
PlatformsCloud, Self-hosted, VPCLinux, Docker, Kubernetes, Self-hosted
CategoryAutomation IntegrationDatabases

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Prefect

  • Python function decorators
  • Automatic resilience
  • Flexible deployment
  • Observable execution
  • Multiple scheduling
  • Webhooks
  • Open-source core

Only in Apache Airflow

  • Pipelines as Python
  • Web UI
  • Cloud provider packages
  • Jinja templating
  • Retries and dependencies
  • Extensible operators

What people use each for

The jobs each tool is most often brought in to do.

Prefect

  • Orchestrating data pipeline workflows in Pythonnot Apache Airflow
  • Managing ML model training and inference jobsnot Apache Airflow
  • Building ETL and event-driven automationnot Apache Airflow
  • Monitoring and alerting on workflow healthnot Apache Airflow

Apache Airflow

  • Scheduling nightly ETL where step order and retries matternot Prefect
  • Coordinating machine learning training and evaluation runsnot Prefect
  • Orchestrating dbt runs alongside extraction and loadingnot Prefect
  • Replacing a sprawl of cron jobs with dependencies and visible run historynot Prefect

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Prefect

  • Limited to Python-based workflows; other languages require API calls
  • Hobby free tier severely limited for production use
  • Team plan billing per user scales quickly with team size
  • Less visual workflow builder compared to some competitors
  • Smaller ecosystem of pre-built connectors than alternatives

Apache Airflow

  • Self-hosting is genuinely heavy: scheduler, metadata database, workers and executor choice are a standing operational job
  • Built for scheduled batch work, and a poor fit for event-driven or sub-minute latency pipelines
  • Because DAGs are Python that the scheduler parses continuously, expensive top-level code in a DAG file slows the whole scheduler
  • Local development and testing of DAGs is awkward compared with newer orchestrators designed with it in mind

Pricing, plan by plan

Prefect

Free
  • HobbyFree
    • 2 users and 5 deployments
    • 500 minutes serverless monthly
    • 7-day run retention
  • Starter$100/month
    • 3 users and 20 deployments
    • 75 hours serverless compute
    • Bring-your-own infrastructure
  • Team$100/user/month
    • 4-8 users per plan tier
    • 100 deployments
    • 225 hours serverless monthly
  • Enterprise$null/custom
    • SSO and SAML authentication
    • Role-based access control
    • Multiple workspaces

Apache Airflow

Free
  • Apache AirflowFree
    • Full scheduler and web UI
    • All provider packages
    • No task or DAG limits

Which should you pick?

Choose Prefect if

  • You need python function decorators.
  • You want to start without paying.
  • You work on Cloud, Self-hosted, VPC.
  • You also want automatic resilience.
Prefect review

Choose Apache Airflow if

  • You need pipelines as python.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want web ui.
Apache Airflow review

Questions people ask

Is Prefect or Apache Airflow better?
Neither clearly leads. Prefect starts at Free and Apache Airflow at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Prefect or Apache Airflow?
Prefect starts at Free and Apache Airflow at Free.
Does Prefect or Apache Airflow run on more platforms?
Prefect runs on Cloud, Self-hosted, VPC. Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted.
Can I use Prefect for free?
Both have a free tier, so you can try either at no cost before committing.
What is Prefect best used for?
Prefect is most often used for orchestrating data pipeline workflows in python, managing ml model training and inference jobs, building etl and event-driven automation, monitoring and alerting on workflow health. Of those, orchestrating data pipeline workflows in python and managing ml model training and inference jobs are not what Apache Airflow is typically brought in for.
What can Prefect do that Apache Airflow cannot?
Prefect covers Python function decorators, Automatic resilience, Flexible deployment, Observable execution. Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating.

Answered from the vendors’ own pages

Prefect: What is included in the Hobby free plan?

Hobby includes 2 users, 5 deployments, 500 minutes of serverless compute monthly, and 7-day run retention.

Source
Apache Airflow: Is Apache Airflow free?

Yes. Airflow is open source under the Apache Software Foundation with no licence fee. Costs are the infrastructure to run it, or a managed service such as Google Cloud Composer or Amazon MWAA.

Prefect: What is the difference between Starter and Team plans?

Starter is $100/month for 3 users and 20 deployments. Team is $100 per user per month for 4-8 users and 100 deployments.

Source
Apache Airflow: What language are Airflow workflows written in?

Python. A workflow is a Python file, so standard language features including loops and datetime handling can generate tasks dynamically, with no XML or command-line configuration.

Prefect: Can I deploy Prefect in my own infrastructure?

Yes, Starter and higher plans support bring-your-own-compute infrastructure and VPC deployments.

Source
Apache Airflow: Is Airflow suitable for real-time pipelines?

Not really. Airflow is designed for scheduled batch orchestration. Event-driven or sub-minute work is better served by a streaming platform such as Kafka or a purpose-built streaming engine.

Apache Airflow: What are the main alternatives to Airflow?

Dagster and Prefect are the two most commonly weighed against it, both newer and both designed around the local development and testing experience Airflow is criticised for.

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