Compare/Apache Airflow vs Dagster

AI tool comparison

Apache Airflow vs Dagster

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

A

Data

Apache Airflow

Programmatic workflow orchestration

Skip

33%

Panel ship

Community

Free

Entry

Apache Airflow is the most popular workflow orchestration platform for data pipelines. DAG-based scheduling with Python. Massive ecosystem but showing its age.

D

Data

Dagster

Data orchestration platform

Ship

100%

Panel ship

Community

Free

Entry

Dagster orchestrates data pipelines with software-defined assets, type checking, and observability. Modern alternative to Airflow with better developer experience.

Decision
Apache Airflow
Dagster
Panel verdict
Skip · 1 ship / 2 skip
Ship · 3 ship / 0 skip
Community
No community votes yet
No community votes yet
Pricing
Free (OSS), managed options vary
Free (OSS), Cloud from $100/mo
Best for
Programmatic workflow orchestration
Data orchestration platform
Category
Data
Data

Reviewer scorecard

Builder
80/100 · ship

The standard for data pipeline orchestration. Massive community, operator ecosystem, and battle-tested at scale.

80/100 · ship

Software-defined assets are the right abstraction. Better DX than Airflow with type checking and built-in observability.

Skeptic
45/100 · skip

Airflow works but its age shows. DAG development is slow, testing is painful, and the UI is dated. Dagster or Prefect are better.

80/100 · ship

The asset-centric approach makes more sense than Airflow's task-centric model for modern data engineering.

Futurist
45/100 · skip

Airflow defined data orchestration but newer tools like Dagster have better abstractions. Inertia keeps Airflow dominant.

80/100 · ship

Dagster represents the next generation of data orchestration. Asset-based thinking replaces task-based thinking.

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