MLflow vs New Relic: Key Differences & When to Use Each
Comprehensive side-by-side comparison of features, pricing, and metrics
Key Differences
Compare MLflow and New Relic across features, pricing, integrations, and community metrics. MLflow / New Relic.
Feature
MLflow
Machine Learning
New Relic
Monitoring
Side-by-side comparison of developer tools
Platform for the machine learning lifecycle
New Relic APM agent for Ruby applications
GitHub Stars
⭐ 25,708
⭐ 1,207
Contributors
👥 1,041
👥 305
Pricing
✓ Free
Enterprise: Contact sales
✓ Free
Enterprise: Contact sales
Languages
Python
Ruby
Features
- • Agentops
- • Agents
- • Ai
- • Ai Governance
- • Apache Spark
- • Agent
- • Apm Agent
- • Hacktoberfest
- • Ruby
Integrations
- • prometheus
No integrations listed
Momentum Score
95/100Momentum959595
(slowing)
19/100Momentum191919
(stable)
Community Health
85/100Health858585
(excellent)
19/100Health191919
(needs-attention)
Maturity Index
63/100Maturity636363
(growing)
15/100Maturity151515
(experimental)
Innovation Score
70/100Innovation707070
(innovative)
16/100Innovation161616
(traditional)
Risk Score (higher is safer)
68/100Risk686868
(low)
29/100Risk292929
(high)
Developer Experience
54/100DX545454
(needs-improvement)
18/100DX181818
(poor)
Links
MLflow Strengths
- ✓ More popular (25,708 stars)
- ✓ Larger community (1,041 contributors)
- ✓ More features (5 listed)
New Relic Strengths
When to Use MLflow vs New Relic
Use MLflow when its strengths align better with your stack and team needs, and choose New Relic when its ecosystem, integrations, or cost profile is a better fit.
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Data source: GitHub API
Last updated: 5/4/2026