Dagster vs Prefect: Diferencas principais e quando usar cada um

Análise abrangente das principais diferenças, casos de uso e sinais da comunidade.

Diferencas principais

Compare Dagster e Prefect em recursos, preco, integracoes e metricas da comunidade. Dagster / Prefect.

Recurso

Dagster

Workflow

Prefect

Workflow

Compare ferramentas para desenvolvedores lado a lado com métricas reais.
Data orchestrator for machine learning and analytics
Modern workflow orchestration
GitHub Stars
⭐ 16.073
⭐ 23.719
Contributors
👥 695
👥 472
Pricing
✓ Grátis
Enterprise: Contact sales
✓ Grátis
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
81/100 (slowing)
71/100 (slowing)
Community Health
51/100 (developing)
34/100 (needs-attention)
Maturity Index
49/100 (emerging)
44/100 (emerging)
Innovation Score
42/100 (evolving)
51/100 (evolving)
Risk Score (higher is safer)
53/100 (low)
43/100 (medium)
Developer Experience
53/100 (needs-improvement)
53/100 (needs-improvement)
Links
🌐 Visitar site Ver no GitHub
🌐 Visitar site Ver no GitHub

Dagster Strengths

  • ✓ Larger community (695 contributors)

Prefect Strengths

  • ✓ More popular (23.719 estrelas)

Quando usar Dagster vs Prefect

Use Dagster quando seus pontos fortes se encaixarem melhor no seu stack e equipe, e escolha Prefect quando ecossistema, integracoes ou custo forem mais adequados.

Related comparisons

Dagster vs Apache Airflow → Prefect vs Apache Airflow → Dagster vs n8n → Prefect vs n8n → Dagster vs Elasticsearch → Prefect vs Playwright → Dagster vs Grafana → Prefect vs Grafana → Dagster vs Redis → Prefect vs Ansible → Dagster vs Prometheus → Prefect vs Prometheus →

More Comparisons

View Dagster → View Prefect → Pesquisar mais ferramentas →

Data source: GitHub API

Última atualização 8/31/2026