head to head · open source
Langfuse vs deep-searcher
Langfuse has 34,826 GitHub stars, 3,815 forks, 926 open issues and last shipped yesterday. deep-searcher has 8,273 stars, 804 forks, 55 open issues and last shipped 10 months ago. Langfuse leads on adoption by 321% (34,826 vs 8,273 stars). Langfuse is written in TypeScript under a custom or non-standard licence; deep-searcher is written in Python under Apache-2.0. Langfuse has attracted 11% as many forks as stars, deep-searcher 10%. Langfuse was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (llm), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| Langfuse | deep-searcher | |
|---|---|---|
| GitHub stars | ★ 35K | ★ 8.3K |
| License | Custom / other | Apache-2.0 |
| Written in | TypeScript | Python |
| Last push | 2026-09-19 | 2025-11-19 |
| Forks | ⑂ 3.8K | ⑂ 804 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Langfuse if
- You weight community size — 35K stars and counting
- You want the Custom / other license terms
- Your stack matches TypeScript
- You value the larger contributor base for long-term maintenance
pick deep-searcher if
- You want the deep-searcher feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and deep-searcher fits your workflow better
About Langfuse
Langfuse is an open source LLM engineering platform for building, monitoring, and improving AI powered applications. It lives in the LLMops ecosystem and provides tooling for the full development lifecycle—from prompt iteration and evaluation to observability and dataset management. Built with TypeScript and powered by ClickHouse, it enables teams to track LLM calls, user sessions, and internal logic like retrieval or agent actions in a unified interface.
read the full Langfuse overview →
About deep-searcher
DeepSearcher is an open source deep research tool that combines large language models with vector databases to search, evaluate, and reason over private data, producing accurate answers and comprehensive reports. Written in Python and released under the Apache 2.0 license, it lives in the AI and machine learning ecosystem as a machine learning infrastructure project, built around agentic retrieval augmented generation and the Zilliz/Milvus vector search stack. The project has been on GitHub for two years, carries 8265 stars and 803 forks, and had its most recent push on 19 November 2025.
read the full deep-searcher overview →
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Frequently asked questions
Is Langfuse or deep-searcher more popular?
Langfuse has 34,826 GitHub stars and deep-searcher has 8,273. Langfuse has the larger community by that measure.
Are Langfuse and deep-searcher free?
Both are open source. Langfuse has no licence declared in this registry, and deep-searcher is licensed under Apache-2.0. Both are free to self-host.
What is the difference between Langfuse and deep-searcher?
Langfuse is written in TypeScript and deep-searcher in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, Langfuse or deep-searcher?
Choose Langfuse if you want the larger community (34,826 stars) or its Custom / other licence terms. Choose deep-searcher if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.