head to head · open source
txtai vs kividb
txtai has 13,029 GitHub stars, 947 forks, 9 open issues and last shipped 3 days ago. kividb has 543 stars, 15 forks, 9 open issues and last shipped yesterday. txtai leads on adoption by 2,299% (13,029 vs 543 stars). txtai is written in Python under Apache-2.0; kividb is written in Rust under AGPL-3.0. txtai has attracted 7% as many forks as stars, kividb 3%. kividb was the more recently maintained of the two, and both are self-hostable with no licence fee.
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 | kividb | |
|---|---|---|
| GitHub stars | ★ 13K | ★ 543 |
| License | Apache-2.0 | AGPL-3.0 |
| Written in | Python | Rust |
| Last push | 2026-10-22 | 2026-10-24 |
| Forks | ⑂ 947 | ⑂ 15 |
| 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 kividb if
- You want the kividb feature set and don't need the biggest community
- You prefer the AGPL-3.0 license terms
- Your stack matches Rust
- You evaluated both and kividb fits your workflow better
About txtai
All in one AI framework txtai is an all in one AI framework for semantic search, LLM orchestration and language model workflows. The key component of txtai is an embeddings database, which is a union of vector indexes (sparse and dense), graph networks and relational databases. This foundation enables vector search and/or serves as a powerful knowledge source for large language model (LLM) applications. Build autonomous agents, retrieval augmented generation (RAG) processes, multi model workflows and more. Summary of txtai features: 🔎 Vector search with SQL, object storage, topic modeling, graph analysis and…
read the full txtai overview →
About kividb
KiviDB KiviDB is a fast, multi threaded alternative to Redis® and Valkey, written in Rust. It speaks the Redis protocol (RESP2 and RESP3), so existing Redis clients, redis cli and libraries work unchanged, and it has full text and vector search built in. It runs every core on a sharded in memory key value design, and persists to snapshots and an optional append only file. On the same 32 cores, KiviDB serves 21 million pipelined GETs per second: about 9× Redis 8 and 2.3× Dragonfly , with under half Dragonfly's p99 latency (benchmarks). KiviDB listens on 6380 , not Redis's 6379, so the two can run side by side…
read the full kividb overview →
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Frequently asked questions
Is txtai or kividb more popular?
txtai has 13,029 GitHub stars and kividb has 543. txtai has the larger community by that measure.
Are txtai and kividb free?
Both are open source. txtai is licensed under Apache-2.0 and kividb under AGPL-3.0. Neither carries a licence fee.
What is the difference between txtai and kividb?
txtai is written in Python and kividb in Rust. 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 kividb?
Choose txtai if you want the larger community (13,029 stars) or its Apache-2.0 licence terms. Choose kividb if its feature set, stack or AGPL-3.0 licence fits better. Both are self-hostable.