Dagster vs Grafana: Key Differences & When to Use Each

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

Key Differences

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

Feature

Dagster

Workflow

Grafana

Monitoring

Side-by-side comparison of developer tools
Data orchestrator for machine learning and analytics
The open and composable observability and data visualization platform
GitHub Stars
⭐ 15,427
⭐ 73,569
Contributors
👥 673
👥 3,006
Pricing
✓ Free
Enterprise: Contact sales
✓ Free
Enterprise: Contact sales
Languages
Python
TypeScript
Features
  • • Analytics
  • • Dagster
  • • Data Engineering
  • • Data Integration
  • • Data Orchestrator
  • • Alerting
  • • Analytics
  • • Business Intelligence
  • • Dashboard
  • • Data Visualization
Integrations
No integrations listed
  • • prometheus
  • • grafana
  • • elasticsearch
Momentum Score
94/100 (stable)
94/100 (stable)
Community Health
50/100 (developing)
95/100 (excellent)
Maturity Index
45/100 (emerging)
90/100 (mature)
Innovation Score
43/100 (evolving)
95/100 (pioneering)
Risk Score (higher is safer)
53/100 (low)
94/100 (minimal)
Developer Experience
54/100 (needs-improvement)
80/100 (good)
Links
🌐 Visit Website View on GitHub
🌐 Visit Website View on GitHub

Dagster Strengths

Grafana Strengths

  • ✓ More popular (73,569 stars)
  • ✓ Larger community (3,006 contributors)

When to Use Dagster vs Grafana

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

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Data source: GitHub API

Last updated: 5/4/2026