Skip to content
SPECIFICTION
Get listed

Apache Airflow vs Dagster

Apache Airflow

airflow.apache.org

Dagster

dagster.io

Side by side

FigureApache AirflowDagster
Price fromFree$10/mo
Free planYes—
Free trial—Yes
Open source——
WebYesYes
macOSYes—
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published16
Spec score · Workload Automation Software8.6 (#4)8.3 (#10)
Spec score · Workflow Orchestration Software8.6 (#8)8.3 (#13)
Spec score · DataOps Platforms8.6 (#5)8.3 (#8)
HeadquartersWilmington, Delaware, U.S.San Francisco, California, United States

Plans

Apache Airflow

  • Apache AirflowFree

Apache Airflow pricing →

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

Dagster pricing →

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.

Visit airflow.apache.org

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.

Visit dagster.io