Registry › Compare › Evidently vs Langfuse

Evidently vs Langfuse

Both are Grade B and 4.9 points apart, so choose on what you weigh most. Evidently leads on supply-chain integrity and provenance; Langfuse leads on maintenance and adoption.

B Evidently 74.3

Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

evidentlyai/evidently · #282 overall · #10 Observability & Evaluation · coverage A (4/5)

Choose Evidently if supply-chain integrity and provenance matter most.

+7.2Identity / Provenance: package provenance attested, against none
+2.5Safety / Integrity: package provenance attested, against none

B Langfuse 79.2

🪢 Open source agent evals & observability: Trace, evaluate, and improve LLM applications with one open platform.

langfuse/langfuse · #193 overall · #6 Observability & Evaluation · coverage A (4/5)

Choose Langfuse if maintenance and adoption matter most.

+10.8Maintenance: last push 1d ago, against 43d ago
+3.6Adoption: 10.0M weekly downloads against 196.5k
+3.0Transparency: OSSF Scorecard 7.1 against 3.5

Where they differ

16.3

Safety / IntegrityEvidently +2.5

13.8

18.0

Identity / ProvenanceEvidently +7.2

10.8

11.5

TransparencyLangfuse +3.0

14.5

9.1

MaintenanceLangfuse +10.8

19.9

16.4

AdoptionLangfuse +3.6

20.0

+3.0

Runtime calibrationEvidently +2.8

+0.2

Full evidence table

An independent, evidence-based trust comparison of Evidently and Langfuse, 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	Evidentlyevidentlyai/evidently	Langfuselangfuse/langfuse
HVTrust score	74.3	79.2
Evidence grade	B	B
Coverage grade	A	A
Overall rank	#282	#193
Rank in Observability & Evaluation	#10	#6
GitHub stars	8.1k	37.3k
Last updated	43d ago	1d ago
Build provenance	Yes	No
OSSF Scorecard	3.5 / 10	7.1 / 10
License	Apache-2.0	NOASSERTION
Downloads	197k/wk	10.0M/wk
Trust dimensions (points earned)
Safety / integrity / 25	16.3	13.8
Identity & provenance / 18	18.0	10.8
Transparency / 17	11.5	14.5
Maintenance / 20	9.1	19.9
Adoption / 20	16.4	20.0
Runtime capability surface (full matrix)
MCP server	—	Implemented
External providers	3 — Multi-provider (LiteLLM), OpenAI, Postgres	2 — Anthropic, OpenAI
Requires API keys	No	Yes
Plugin surface	—	plugins
Provenance drift	Match	Unknown

Open in the live compare tool → Evidently profile Langfuse 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 →