Apache Airflow vs Dagster
Apache Airflow
airflow.apache.orgDagster
dagster.ioSide by side
| Figure | Apache Airflow | Dagster |
|---|---|---|
| Price from | Free | $10/mo |
| Free plan | Yes | — |
| Free trial | — | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 6 |
| Spec score · Workload Automation Software | 8.6 (#4) | 8.3 (#10) |
| Spec score · Workflow Orchestration Software | 8.6 (#8) | 8.3 (#13) |
| Spec score · DataOps Platforms | 8.6 (#5) | 8.3 (#8) |
| Headquarters | Wilmington, Delaware, U.S. | San Francisco, California, United States |
Plans
Dagster
- Solo$10 a month
- Starter$100 a month
- ProPriced on request
- Solo Plan$10 a month
- Starter Plan$100 a month
- Pro PlanPriced on request
In their own words
Apache Airflow
Apache Airflow is a platform for authoring, scheduling, and monitoring workflows written in Python. It is designed for batch workflows with a defined beginning and end that run on a schedule. Its web application lets users manage and schedule workflows, trigger DAGs manually, inspect task status and logs, backfill runs, and rerun failed tasks. A modular architecture uses a message queue to coordinate workers and can orchestrate an arbitrary number of them. Built-in operators connect workflows to Google Cloud Platform, Amazon Web Services, Microsoft Azure, and other services. The community maintains more than 80 separately installable provider packages, which can be upgraded or downgraded independently of Airflow core. Airflow can read connections, variables, and configuration from secret backends, but those integrations do not support writes. JWT authentication is used for its public REST API and internal Execution API. From Airflow 3 onward, sensitive credentials are masked in logs, the interface, and API output. Airflow is free to download and use under the Apache License.
Dagster
Dagster is a data-aware orchestrator for building, running and monitoring data pipelines and assets. It models assets and dependencies to show lineage across a data platform, while supporting partitions, incremental runs, declarative workflows and fault-tolerant orchestration. An integrated catalog combines data discovery, lineage, workflows and operational metadata. Quality features include code-embedded validation, automated testing, freshness checks and observability tools. The integration directory lists Airbyte, Anthropic, Apache Airflow, AWS services and Azure Data Lake Storage. Dagster+ hybrid deployment keeps compute in a customer’s infrastructure while Dagster manages the control plane. The core framework is open source on GitHub. Platforms listed are API, Linux, self-hosted and web; deployment is hybrid. A 30-day trial is listed. Solo costs $10 a month plus usage charges, and Starter costs $100 a month plus usage charges. Dagster’s website says it is now part of Prefect.