Apache Airflow vs Logstash: Key Differences & When to Use Each

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

Key Differences

Compare Apache Airflow and Logstash across features, pricing, integrations, and community metrics. Apache Airflow / Logstash.

Feature

Apache Airflow

Workflow

Logstash

Logging

Side-by-side comparison of developer tools
Platform to programmatically author and schedule workflows
Server-side data processing pipeline
GitHub Stars
⭐ 45,276
⭐ 14,845
Contributors
👥 4,323
👥 613
Pricing
✓ Free
Enterprise: Contact sales
✓ Free
Enterprise: Contact sales
Languages
Python
Java
Features
  • • Airflow
  • • Apache
  • • Apache Airflow
  • • Automation
  • • Dag
  • • Etl Framework
  • • Java
  • • Jruby
  • • Logging
  • • Real Time Processing
Integrations
No integrations listed
No integrations listed
Momentum Score
94/100 (stable)
47/100 (stable)
Community Health
91/100 (excellent)
34/100 (needs-attention)
Maturity Index
88/100 (mature)
50/100 (emerging)
Innovation Score
88/100 (pioneering)
52/100 (evolving)
Risk Score (higher is safer)
94/100 (minimal)
53/100 (low)
Developer Experience
80/100 (good)
54/100 (needs-improvement)
Links
🌐 Visit Website View on GitHub
🌐 Visit Website View on GitHub

Apache Airflow Strengths

  • ✓ More popular (45,276 stars)
  • ✓ Larger community (4,323 contributors)

Logstash Strengths

When to Use Apache Airflow vs Logstash

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

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Data source: GitHub API

Last updated: 5/4/2026