Dagster vs Apache Flink: Key Differences & When to Use Each

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

Key Differences

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

Feature

Dagster

Workflow

Apache Flink

Data Processing

Side-by-side comparison of developer tools
Data orchestrator for machine learning and analytics
Stream processing framework
GitHub Stars
⭐ 15,427
⭐ 25,980
Contributors
👥 673
👥 2,096
Pricing
✓ Free
Enterprise: Contact sales
✓ Free
Enterprise: Contact sales
Languages
Python
Java
Features
  • • Analytics
  • • Dagster
  • • Data Engineering
  • • Data Integration
  • • Data Orchestrator
  • • Big Data
  • • Flink
  • • Java
  • • Python
  • • Scala
Integrations
No integrations listed
No integrations listed
Momentum Score
94/100 (stable)
79/100 (stable)
Community Health
50/100 (developing)
68/100 (moderate)
Maturity Index
45/100 (emerging)
82/100 (established)
Innovation Score
43/100 (evolving)
76/100 (innovative)
Risk Score (higher is safer)
53/100 (low)
87/100 (minimal)
Developer Experience
54/100 (needs-improvement)
68/100 (fair)
Links
🌐 Visit Website View on GitHub
🌐 Visit Website View on GitHub

Dagster Strengths

Apache Flink Strengths

  • ✓ More popular (25,980 stars)
  • ✓ Larger community (2,096 contributors)

When to Use Dagster vs Apache Flink

Use Dagster when its strengths align better with your stack and team needs, and choose Apache Flink 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