Astro by Astronomer
Data fabric software
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What is Astro by Astronomer
Astro by Astronomer is a managed platform for orchestrating, scheduling, and operating data pipelines using Apache Airflow. It targets data engineering and analytics teams that need to deploy Airflow reliably across cloud environments, manage DAGs and dependencies, and standardize operational practices. The product emphasizes Airflow-native development with managed infrastructure, CI/CD-oriented workflows, and operational tooling for running and monitoring pipelines at scale.
Managed Apache Airflow operations
Astro provides a managed control plane for running Apache Airflow, reducing the need to self-manage schedulers, workers, upgrades, and scaling. It supports common operational needs such as environment management and version control alignment for DAG deployments. For teams standardizing on Airflow, this keeps orchestration consistent while shifting infrastructure responsibilities to the vendor.
Strong orchestration and scheduling
Airflow-based orchestration supports complex dependency graphs, retries, SLAs, and time-based scheduling patterns that are common in analytics and ELT workloads. Astro inherits the Airflow ecosystem of operators and integrations, which helps connect to many data stores and services. This makes it well-suited for coordinating multi-step workflows across heterogeneous systems.
Developer workflow and governance
Astro is designed to fit CI/CD-style development for pipelines, including promotion across environments and repeatable deployments. It supports team-based operations where multiple engineers collaborate on DAGs and need consistent runtime behavior. This can improve operational discipline compared with ad hoc scripting or manually managed schedulers.
Not a full integration suite
Astro focuses on orchestration rather than providing a broad library of managed connectors, transformation engines, or end-to-end integration design tooling. Teams typically still need separate tools for ingestion, ELT/ETL transformations, cataloging, and governance. As a result, it may not replace broader data integration platforms or data fabric products on its own.
Airflow complexity and overhead
Airflow’s DAG authoring and operational model can be complex for teams without Python and workflow-orchestration experience. Some use cases (e.g., near-real-time streaming, event-driven micro-orchestration) may require additional components or different patterns than batch-oriented scheduling. Operational best practices (testing, dependency management, backfills) still require engineering effort even on a managed service.
Observability is pipeline-centric
Astro monitoring primarily centers on workflow execution (task status, retries, logs) rather than comprehensive data observability across datasets (freshness, schema drift, lineage, and quality rules) without additional tooling. Organizations seeking unified metadata management and governance may need separate platforms. This can increase toolchain complexity for enterprises aiming for a single pane of glass.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Developer | Deployments starting at $0.35 per hour (pay-as-you-go, billed monthly) | SAML-based SSO; flexible scale-to-zero compute; hibernating deployments; deployment rollbacks; alerting; API access; non-owner roles. "Try for Free" is offered. |
| Team | Deployments starting at $0.42 per hour (pay-as-you-go, billed monthly; also available via annual agreements) | Everything in Developer plus: network isolation; dedicated clusters; audit logging (7-day retention); high availability deployments; 24x5 support. "Try for Free" is offered. |
| Business | Contact Astronomer for pricing (Get a Quote) | Annual agreements; everything in Team plus SSO enforcement; CI/CD enforcement; audit logging (90-day retention); 24x7 support (1 hour SLA). |
| Enterprise | Contact Astronomer for pricing (Get a Quote) | Annual agreements; everything in Business plus SCIM provisioning; custom RBAC; IP access list; organization dashboards; additional enterprise controls. |
Additional usage-based components (listed on Astronomer pricing page):
Cluster Pricing:
- Standard: Included on all Plans.
- Dedicated: Starts at $2.40 per hour on Team.
Deployment Pricing (standard, Developer-plan example prices; prices reflect AWS us-east-1/Azure eastus/GCP us-east1):
- Standard - Small: $0.35 per hour (1 scheduler replica, 1 vCPU, 2 GiB memory).
- Standard - Medium: $0.57 per hour.
- Standard - Large: $0.77 per hour.
- Standard - Extra Large: $1.54 per hour.
High Availability Deployment Pricing (Developer-plan example):
- HA Small: $0.70 per hour.
- HA Medium: $1.14 per hour.
- HA Large: $1.54 per hour.
- HA Extra Large: $3.08 per hour.
Worker Pricing (Developer-plan example per worker hour):
- A5 (1 vCPU, 2 GiB): $0.13 per hour.
- A10 (2 vCPU, 4 GiB): $0.26 per hour.
- A20 (4 vCPU, 8 GiB): $0.52 per hour.
- A40 (8 vCPU, 16 GiB): $1.04 per hour.
- A60 (12 vCPU, 24 GiB): $1.56 per hour.
- A120 (24 vCPU, 48 GiB): $3.12 per hour.
- A160 (32 vCPU, 64 GiB): $4.16 per hour.
Other notes:
- Networking costs are passed through from the cloud provider and prices shown reflect specific regions (AWS us-east-1, Azure eastus, GCP us-east1).
- Astro AI: $10 in usage included per org per month; prompt tokens $3.75 per million; response tokens $18.75 per million (public preview).
Seller details
Astronomer, Inc.
Cincinnati, Ohio, USA
2018
Private
https://www.astronomer.io/
https://x.com/astronomerio
https://www.linkedin.com/company/astronomer/
