head to head · open source

txtai vs knowhere

txtai has 12,964 GitHub stars, 891 forks, 9 open issues and last shipped 5 days ago. knowhere has 3,388 stars, 322 forks, 40 open issues and last shipped 3 days ago. txtai leads on adoption by 283% (12,964 vs 3,388 stars). txtai is written in Python under Apache-2.0; knowhere is written in Python under Apache-2.0. txtai has attracted 7% as many forks as stars, knowhere 10%. knowhere was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (ai-agents), 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.

txtai ★ 13K knowhere ★ 3.4K category AI & Machine Learning

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Side by side

txtai knowhere
GitHub stars ★ 13K ★ 3.4K
License Apache-2.0 Apache-2.0
Written in Python Python
Last push 2026-09-15 2026-09-17
Forks ⑂ 891 ⑂ 322
Self-hosting Yes Yes
Data ownership Your server Your server

pick txtai if

  • You weight community size — 13K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full txtai profile →

pick knowhere if

  • You want the knowhere 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 knowhere fits your workflow better

full knowhere profile →

About txtai

txtai is an all in one AI framework for semantic search, LLM orchestration and language model workflows, written in Python and released under the Apache 2.0 license. It lives in the Python machine learning ecosystem and is built on Hugging Face Transformers, Sentence Transformers and FastAPI. The core component is an embeddings database, which is a union of vector indexes (both sparse and dense), graph networks and relational databases. That foundation enables vector search and also serves as a knowledge source for large language model applications.

read the full txtai overview →

About knowhere

Knowhere is an Apache 2.0 Python document parsing and retrieval system that turns complex, dirty files into persistent, navigable memory for AI agents and RAG pipelines, built for developers and teams assembling Agentic RAG, vector based RAG, or other LLM workflows over local and offline document collections.

read the full knowhere overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 157K Open WebUI ★ 153K langchain ★ 147K

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Compare either of these against the rest of the Machine Learning Infrastructure field.

txtai vs Ollama txtai vs llama.cpp txtai vs vllm txtai vs GPT4All txtai vs llama_index txtai vs LocalAI txtai vs faiss txtai vs PageIndex txtai vs Langfuse txtai vs cognee txtai vs taipy txtai vs dagster

Frequently asked questions

Is txtai or knowhere more popular?

txtai has 12,964 GitHub stars and knowhere has 3,388. txtai has the larger community by that measure.

Are txtai and knowhere free?

Both are open source. txtai is licensed under Apache-2.0 and knowhere under Apache-2.0. Neither carries a licence fee.

What is the difference between txtai and knowhere?

txtai is written in Python and knowhere 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, txtai or knowhere?

Choose txtai if you want the larger community (12,964 stars) or its Apache-2.0 licence terms. Choose knowhere if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.