Registry › Compare › Arize Phoenix vs MLflow

Arize Phoenix vs MLflow

MLflow leads on trust: 89.6/100 (Grade A) against 76.5/100 (Grade B), a 13.1-point gap. MLflow leads on supply-chain integrity and transparency.

B Arize Phoenix 76.5

AI Observability & Evaluation

Arize-AI/phoenix · #202 overall · #9 Observability & Evaluation · coverage A (4/5)

Arize Phoenix doesn't lead on any scored dimension in this pair.

A MLflow 89.6

The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.

mlflow/mlflow · #22 overall · #2 Observability & Evaluation · coverage A (4/5)

Choose MLflow if supply-chain integrity and transparency matter most.

+7.1Safety / Integrity: 100% of recent commits signed, against 96%
+4.7Transparency
+3.0Adoption: 4.7M weekly downloads against 145.1k

Where they differ

12.3

Safety / IntegrityMLflow +7.1

19.4

8.5

TransparencyMLflow +4.7

13.2

19.9

MaintenanceMLflow +0.1

20.0

16.6

AdoptionMLflow +3.0

19.6

+1.2

Runtime calibrationArize Phoenix +1.8

-0.6

1 dimension identical: Identity 18.0 · Full evidence table

An independent, evidence-based trust comparison of Arize Phoenix and MLflow, two Observability & Evaluation projects in the HVTracker registry. Scores come from public, checkable signals — supply-chain provenance, OSSF Scorecard, maintenance, and adoption — not popularity.

Full evidence

Signal	Arize PhoenixArize-AI/phoenix	MLflowmlflow/mlflow
HVTrust score	76.5	89.6
Evidence grade	B	A
Coverage grade	A	A
Overall rank	#202	#22
Rank in Observability & Evaluation	#9	#2
GitHub stars	11.7k	28.2k
Last updated	1d ago	today
Build provenance	Yes	Yes
OSSF Scorecard	—	5.5 / 10
License	NOASSERTION	Apache-2.0
Downloads	145k/wk	4.7M/wk
Trust dimensions (points earned)
Safety / integrity / 25	12.3	19.4
Identity & provenance / 18	18.0	18.0
Transparency / 17	8.5	13.2
Maintenance / 20	19.9	20.0
Adoption / 20	16.6	19.6
Runtime capability surface (full matrix)
MCP server	Implemented	Implemented
External providers	6 — Amazon Bedrock, Anthropic, E2B, …	3 — Amazon Bedrock, Anthropic, Postgres
Requires API keys	No	No
Plugin surface	plugins	plugins
Provenance drift	Partial	Unknown

Open in the live compare tool → Arize Phoenix profile MLflow profile More Observability & Evaluation →

How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption, scaled by an evidence-confidence factor. Grade bands: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Signals refresh daily. Full methodology v4.4 →