Langfuse vs. Arize AX / Arize Phoenix
This guide outlines the key differences between Langfuse and Arize AX to help engineering teams choose the right LLM observability platform.
TL;DR:
- Choose Langfuse if you prioritize open-source flexibility, transparent pricing based on usage, and a developer-first experience with extensive integrations and full self-hosting capabilities.
- Choose Arize AX if you need a managed SaaS solution with specialized support for financial compliance (PCI DSS) and deep integration into existing ML data fabrics.
Open Source & Distribution
Langfuse stands out for its open-source model, ensuring feature parity between self-hosted and cloud versions. Arize AX is a proprietary enterprise SaaS, while its open-source counterpart (Arize Phoenix) is primarily for local testing and debugging (uses PostgreSQL instead of ClickHouse).
| Feature | Langfuse | Arize AX |
|---|---|---|
| Model | Open Source (MIT License) | Proprietary SaaS (Open-source “Phoenix” is for local dev only) |
| GitHub Stars |  |  |
| PyPI Downloads |  |  |
| npm Downloads |  | N/A |
| Docker Pulls |  |  |
| Self-Hosting | First-Class Citizen: Full feature parity with Cloud (including ClickHouse). Easy to deploy via Docker. | Limited, Phoenix only. No feature parity with Arize AX Cloud. |
Scalability & Performance
Both tools are built for scale, but they use different architectural approaches. Langfuse is part of ClickHouse and leverages the speed of ClickHouse architecture, while Arize AX uses a proprietary database.
| Feature | Langfuse | Arize AX |
|---|---|---|
| Backend | ClickHouse (acquired Langfuse): Optimized for high-throughput OLAP. | adb (Arize Database): Proprietary engine for agentic telemetry. |
Integrations
Langfuse focuses on broad, community-driven compatibility via OpenTelemetry, whereas Arize AX emphasizes auto-instrumentation and deep data warehouse links.
| Feature | Langfuse | Arize AX |
|---|---|---|
| Standard | OpenTelemetry Native: Built on OTel standards. | OpenTelemetry Native: Built on OTel standards. |
| Frameworks | 80+ Frameworks: with popular frameworks like LangChain, LlamaIndex, OpenAI, Anthropic, etc. | Maintains integrations via OpenInference library. |
Pricing
Langfuse offers a transparent, volume-based pricing model that scales predictably. Arize AX charges based on span counts and data volume, which can become costly for data-heavy LLM apps.
| Feature | Langfuse | Arize AX |
|---|---|---|
| Model | Usage-Based: Billable unit = trace, observation, or score. | Hybrid: Spans + Data Ingestion Volume (GB). |
| Free Tier | 50k traces/mo free to test the full platform. | 25k spans/mo and 1 GB data. |
| Scalability | Graduated pricing (e.g., $6/100k units at scale). Transparent overages. | N/A |
| Plans | Free, Core ($29/mo), Pro ($199/mo), Teams, Enterprise. | Free, Pro ($50/mo), Enterprise. |
Open Platform & Extensibility
Langfuse is designed as a core infrastructure component, allowing teams to build custom internal tools on top of its API.
| Feature | Langfuse | Arize AX |
|---|---|---|
| API Access | API first for all data (traces, evals, prompts) and platform features. | API available, to export to data warehouses. |
| Customizability | Build custom workflows, evaluations, and dashboards using the SDK/API. | Custom evaluations and pipelines via SDK. |
| Data Access | Query via API and blob storage exports. | Query via API and blob storage exports. |
Enterprise Security
Both platforms serve large enterprises, but Arize AX has a slight edge in specific financial certifications (PCI DSS). Langfuse supports masking to filter out PCI DSS sensitive data.
| Feature | Langfuse | Arize AX |
|---|---|---|
| Certifications | SOC 2 Type II, ISO 27001, GDPR, HIPAA aligned. | SOC 2 Type II, HIPAA, PCI DSS 4.0, CSA Star Level 1. |
| Adoption | Trusted by 19 of Fortune 50 & 63 of Fortune 500. | Strong enterprise adoption, particularly in fintech. |
| Governance | SSO, RBAC, Audit Logs available in Teams/Enterprise plans. | SSO, RBAC available in Enterprise plans. |
Feature Highlights
Langfuse:
- Core Observability: Best-in-class tracing with accurate token and cost tracking for 100+ models.
- Prompt Management: Collaborative playground with versioning, caching, fallbacks, and protected labels.
- Collaboration: Annotation queues, comments with @mentions, and audit logs.
- Evaluations: Flexible “LLM-as-a-Judge” evaluators that can be run in-UI or via SDK pipelines.
Arize AX:
- Agentic Visualization: Specialized views for multi-agent conversation flows.
- Data Fabric: Seamless integration with enterprise data lakes (Snowflake/BigQuery).
- Evaluation: Strong focus on session-level evaluation and retrieval diagnosis (RAG).
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