Build Dynamic Data Workflows

Automate and run custom data workflows in minutes using Astronomer's managed Apache Airflow platform.
Greg Neiheisel, Astronomer CTO, demonstrates how Astronomer works with Apache Airflow.
code

Define workflows in code.

Author all standard or custom data pipelines in Python for maintenance, versioning, portability, extensibility and collaboration.

dag

Connect anything.

Build scheduled, dependency-based data pipelines to centralize and route data from any source to any destination.

automate

Automate processes.

Fuel data warehousing, ETL, analytics, experimentation, targeting, sessionization, data infrastructure maintenance and more.

Built on open source. Ready to scale.

Why use Astronomer to run Apache Airflow?
Just Apache Airflow
Astronomer Cloud
Setup in weeks
Time to Production
Setup in minutes
Time to Production
It's on you
Deployment / Hosting
Fully managed cloud
Deployment / Hosting
It's on you
Scaling
Parallel tasks, on-demand
Scaling
It's on you
DAG Deployment
CLI Tools
DAG Deployment
It's on you
Python Dependencies and Packages
Our standard, optimized list
Python Dependencies and Packages
Custom and open source Astronomer plugins
Plugins
Custom and open source Astronomer plugins
Plugins
Email alerts and custom configured DAGs
Monitoring
Email alerts and custom configured DAGs
Monitoring
It's on you
Apache Airflow Support
Basic support included, with custom services available
Apache Airflow Support
Looking for more? Run Astronomer Enterprise in-house to make Apache Airflow accessible to your whole team.
Explore Astronomer Enterprise >

For Developers

Astronomer's Open Edition gives full CLI access to experiment and run our open source, dockerized platform on your own own machine.

"We leverage Astronomer to run Apache Airflow in a SaaS, hosted environment; freeing up engineering and infrastructure resources. Astronomer provides us a highly scalable and flexible Airflow instance without the mess of having to deal with devops. Their customer service is excellent, responsive and incredibly reliable."

— Yang Wang (Data Engineering Product Manager, Karmic Labs)

Ready to get started?

Sign up now—and start building python workflows in minutes.