Migration support available
Teams switching from Astronomer or self-hosted Airflow report 70%+ infrastructure savings
Teams that have made the switch












Built for how teams work today
Write workflows as pure Python functions with simple decorators. Your code runs as-is in your infrastructure with hybrid orchestration.
Create tasks based on data and conditions. No static DAGs required. Your pipeline adapts to reality.
Orchestration separate from execution. Your workflows run in your infrastructure—Kubernetes, ECS, or any compute.
Legacy platform built around static DAGs with framework-specific operators. Centralized scheduler architecture creates performance bottlenecks and requires dedicated infrastructure with complex deployment patterns.
Cost efficiency
Airflow's centralized scheduler and multi-component architecture requires dedicated infrastructure. Prefect's hybrid model separates orchestration from execution—you only run compute when workflows execute in your infrastructure.
Endpoint: 73.78% cost reduction
Rent The Runway: 70% savings
No scheduler infrastructure overhead
Developer experience
Prefect runs your Python as-is with simple decorators. Airflow requires restructuring into DAG objects, operators, and XCom for data passing. Write less boilerplate in your infrastructure.
View Python examplesPrefect
Airflow
Security & control
Prefect Cloud provides orchestration while your workflows execute in your environment. Workers poll via outbound-only connections—no inbound access to your network. Your code, data, and secrets stay on your infrastructure.
Deploy on Kubernetes, ECS, Docker
No data egress, zero code transmission
SOC 2 Type II, GDPR, HIPAA ready
Prefect Cloud hosts the Control Plane & Metadata. You host execution & data.
Beyond ETL
Airflow was designed for traditional ETL. Prefect supports data engineering, ML training, AI inference pipelines, and modern data workloads—all running in your infrastructure with flexible orchestration.
"Airflow was no longer viable for ML workflows. We needed security and ease of adoption."
— Wendy Tang, Machine Learning Engineer, Cash App
Modern orchestration for modern teams
Comprehensive monitoring and real-time dashboards included. Airflow requires external tools like Prometheus and Grafana.
React to events in real-time. Airflow relies on polling, adding latency to your workflows in your infrastructure.
Built-in caching with automatic rollback on failure. Clean recovery without manual intervention.
Develop and test locally before deploying to your infrastructure. No complex setup required.
Works wherever Python runs. Airflow needs multi-component infrastructure with dedicated servers.
Decentralized architecture scales workflows individually in your infrastructure without bottlenecks.
See how Prefect compares across key capabilities
| Feature | Prefect | Airflow |
|---|---|---|
| Pure Python workflows | ||
| Local development & testing | ||
| Minimal learning curve | ||
| Easy debugging & code organization |
| Feature | Prefect | Airflow |
|---|---|---|
| Dynamic DAGs at runtime | ||
| Conditional logic & loops | ||
| Event-driven triggers | Polling only |
| Feature | Prefect | Airflow |
|---|---|---|
| Decentralized architecture | Centralized | |
| Transactional semantics & rollback | ||
| Built-in caching |
From Fortune 500 to high-growth startups

Migrated from Airflow for fraud prevention with enterprise security and data control
Tripled production while dramatically reducing spend by switching infrastructure
Tasks, dependencies, retries, and mapping make robust pipelines easy to write.
The Data Engineering and MLOps teams were impressed by the elimination of retrofitting requirements. Switching from Astronomer to Prefect resulted in a 73.78% reduction in invoice costs alone.
Prefect gives us the granular flexibility to build a custom platform that would work for our entire organization, without needing a bloated infra architecture.
Our job is to provide data analysts and data scientists the data they need to create data products that drive business value. And beyond that, we focus on enabling our data scientists by removing roadblocks and giving them powerful tools that make their jobs easier. Prefect is allowing us to achieve these objectives.
We use Prefect to orchestrate dbt Cloud jobs alongside other data tools. It brings visibility to our entire pipeline and streamlines deployments.
We'll help you migrate to Prefect with dedicated support. Join teams saving 70%+ on infrastructure costs while gaining better performance.
Start free with 2 users and 5 workflows. Your code and data stay in your environment. No credit card required.