Dagster

Open-source asset-centric data orchestration for building and managing data pipelines.

Best for: Asset-centric approach Not ideal for: Learning curve
Price Paid
Free plan Yes
For Operations teams
Level Beginner
Updated Mar 2026
Category AI Automation
01

Why choose Dagster

Open-source data orchestration platform for building, testing, and managing data pipelines. Asset-centric approach to data engineering with built-in testing, observability, and software-defined assets. Dagster Cloud offers managed infrastructure.

  • +Asset-centric approach
  • +Excellent testing
  • +Strong type system
  • +Good documentation
02

Where it falls short

  • Learning curve
  • Smaller ecosystem than Airflow
  • Python-only
  • Resource intensive
03

Best for these users

👤
Target audience
Operations teams, no-code builders, power users
📌
Best for
Asset-centric approach
Skip if you need
Learning curve
04

Pricing overview

Freemium Free plan: Yes

Free open source. Dagster Cloud free tier. Plus from $100/mo. Pro custom pricing.

Check current pricing →
05

Key features

Asset-centric orchestration
Software-defined assets
Built-in testing
Observability
Partitions
Type system
07

Alternatives to Dagster

Apache Airflow

Industry-standard open-source workflow orchestration with Python-based DAGs.

Inngest

Event-driven serverless workflow engine for reliable background jobs and step functions.

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Kestra

Open-source YAML-based declarative workflow orchestration with event-driven architecture.

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Prefect

Python-native workflow orchestration for data engineering and ML pipelines.

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Temporal

Open-source durable execution platform for reliable distributed workflows.

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See all alternatives →
08

Related comparisons

09

The verdict

Dagster Freemium

Dagster is a solid choice for operations teams who need asset-centric approach. At freemium, it delivers good value. Main caveat: learning curve. Compare with alternatives before committing.