Dagster vs Prefect: Key Differences & When to Use Each

Comprehensive side-by-side comparison of features, pricing, and metrics

Key Differences

Compare Dagster and Prefect across features, pricing, integrations, and community metrics. Dagster / Prefect.

Feature

Dagster

Workflow

Prefect

Workflow

Side-by-side comparison of developer tools
Data orchestrator for machine learning and analytics
Modern workflow orchestration
GitHub Stars
⭐ 15,427
⭐ 22,297
Contributors
👥 673
👥 430
Pricing
✓ Free
Enterprise: Contact sales
✓ Free
Enterprise: Contact sales
Languages
Python
Python
Features
  • • Analytics
  • • Dagster
  • • Data Engineering
  • • Data Integration
  • • Data Orchestrator
  • • Automation
  • • Data
  • • Data Engineering
  • • Data Ops
  • • Data Science
Integrations
No integrations listed
No integrations listed
Momentum Score
94/100 (stable)
58/100 (slowing)
Community Health
50/100 (developing)
30/100 (needs-attention)
Maturity Index
45/100 (emerging)
45/100 (emerging)
Innovation Score
43/100 (evolving)
43/100 (evolving)
Risk Score (higher is safer)
53/100 (low)
44/100 (medium)
Developer Experience
54/100 (needs-improvement)
36/100 (poor)
Links
🌐 Visit Website View on GitHub
🌐 Visit Website View on GitHub

Dagster Strengths

  • ✓ Larger community (673 contributors)

Prefect Strengths

  • ✓ More popular (22,297 stars)

When to Use Dagster vs Prefect

Use Dagster when its strengths align better with your stack and team needs, and choose Prefect when its ecosystem, integrations, or cost profile is a better fit.

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More Comparisons

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Data source: GitHub API

Last updated: 5/4/2026