head to head · open source
txtai vs vearch
txtai has 12,964 GitHub stars, 891 forks, 9 open issues and last shipped 5 days ago. vearch has 2,327 stars, 365 forks, 170 open issues and last shipped 2 months ago. txtai leads on adoption by 457% (12,964 vs 2,327 stars). txtai is written in Python under Apache-2.0; vearch is written in Python under Apache-2.0. txtai has attracted 7% as many forks as stars, vearch 16%. txtai was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (embeddings, rag, retrieval-augmented-generation), 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
| txtai | vearch | |
|---|---|---|
| GitHub stars | ★ 13K | ★ 2.3K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-15 | 2026-07-27 |
| Forks | ⑂ 891 | ⑂ 365 |
| 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
pick vearch if
- You want the vearch 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 vearch fits your workflow better
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 vearch
Vearch is an Apache 2.0 cloud native distributed vector database that provides similarity search over embedding vectors for AI native applications, built for teams that need retrieval, RAG, or visual search at a scale where an in process library is no longer enough.
read the full vearch overview →
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Frequently asked questions
Is txtai or vearch more popular?
txtai has 12,964 GitHub stars and vearch has 2,327. txtai has the larger community by that measure.
Are txtai and vearch free?
Both are open source. txtai is licensed under Apache-2.0 and vearch under Apache-2.0. Neither carries a licence fee.
What is the difference between txtai and vearch?
txtai is written in Python and vearch 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 vearch?
Choose txtai if you want the larger community (12,964 stars) or its Apache-2.0 licence terms. Choose vearch if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.