Astronomer
Apache Airflow orchestration platform for data, ML, and AI pipelines at scale.
About Astronomer
Astronomer provides Astro, a unified orchestration platform built on Apache Airflow for building, running, and observing data, ML, and AI pipelines at enterprise scale. The platform empowers data teams to accelerate the creation of reliable data products while managing complex workflows. Designed for enterprises managing DataOps, Astronomer positions itself as the leading solution for orchestrating data and AI pipelines, combining the flexibility of open-source Apache Airflow with managed enterprise features. A notable limitation is that users must have familiarity with Apache Airflow concepts and DAG (Directed Acyclic Graph) development to fully leverage the platform.
At a glance
- Company
- Astronomer (est. 2018)
- Platforms
- Web, Cloud
- Last verified
- June 2026
Who It's For
- •Enterprise data teams and organizations
- •Data engineers managing complex workflows
- •ML/AI teams requiring pipeline orchestration
- •Organizations adopting DataOps practices
How It Works
- 1Built on Apache Airflow, an open-source orchestration engine
- 2Enables users to define, schedule, and monitor data pipelines as code
- 3Provides a managed cloud platform to run Airflow workflows at scale
- 4Offers observability and monitoring capabilities for pipeline execution
How to Use Astronomer
- 1Build data pipelines using Apache Airflow's Python-based DAG definitions
- 2Deploy workflows to the Astro platform for managed orchestration
- 3Monitor and observe pipeline execution through the Astro dashboard
- 4Scale pipelines reliably across distributed infrastructure
Key Features
- •Apache Airflow-based orchestration engine
- •Managed cloud platform for running workflows
- •Built-in observability and monitoring
- •Enterprise-grade data orchestration capabilities
Use Cases
- •Enterprise data pipeline orchestration and workflow management
- •ML pipeline automation and scheduling
- •DataOps platform for managing complex data workflows
- •AI pipeline orchestration at scale
Pros & Cons
Advantages
- •Leverages Apache Airflow, the industry-standard open-source orchestration engine, providing flexibility and widespread adoption
- •Designed specifically for enterprise AI and ML pipeline needs with dedicated platform support
- •Positioned as a unified orchestration platform addressing the rapidly growing DataOps market
Disadvantages
- •Requires understanding of Apache Airflow and DAG-based workflow definitions, creating a learning curve for new users
- •Limited information available about pricing and specific enterprise tier features
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Frequently Asked Questions
What is Astronomer?
Astronomer provides Astro, a unified orchestration platform built on Apache Airflow for building, running, and observing data, ML, and AI pipelines at enterprise scale. The platform empowers data teams to accelerate the creation of reliable data products while managing complex workflows.
How much does Astronomer cost?
Astronomer uses custom pricing — contact the vendor for a quote.
Is Astronomer free?
Astronomer is a paid tool and does not offer a free plan.
What are the best Astronomer alternatives?
Popular Astronomer alternatives include AirOps, Inngest, Dagster.
What is Astronomer used for?
Astronomer is commonly used for Enterprise data pipeline orchestration and workflow management, ML pipeline automation and scheduling, DataOps platform for managing complex data workflows.
What platforms does Astronomer support?
Astronomer is available on Web, Cloud.
Information Accuracy
Please note: While we regularly update all tool information including descriptions, features, pricing, and other details, this information may change over time as tools evolve and update their offerings. For the most current and accurate information, we recommend visiting the official website directly. Our goal is to provide you with comprehensive and up-to-date information to help you make informed decisions.