---
title: Compare Langfuse to other solutions
seoTitle: "Compare Langfuse with other AI engineering platforms"
description: Head-to-head comparisons of Langfuse with other AI engineering and observability platforms.
---

# Compare Langfuse to other solutions

Start with [Why Langfuse?](/why) for a summary of how we position the product. For more context, see our [mission](/handbook/chapters/mission) and [roadmap](/docs/roadmap).

We publish these comparisons to help you make an educated choice. Each page is sourced from public documentation and dated so you can see when we last checked the facts. We are committed to keeping them up to date — [pull requests](https://github.com/langfuse/langfuse-docs) are welcome.

- [LangSmith](/compare/langsmith)
- [Braintrust](/compare/braintrust)
- [Arize / Phoenix](/compare/arize-phoenix)
- [Galileo](/compare/galileo)
- [Datadog Agent Observability](/compare/datadog)

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---

## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/compare.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx @langfuse/cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.