head to head · open source
llama_index vs lancedb
llama_index has 52,202 GitHub stars, 8,162 forks, 770 open issues and last shipped yesterday. lancedb has 11,449 stars, 1,053 forks, 627 open issues and last shipped yesterday. llama_index leads on adoption by 356% (52,202 vs 11,449 stars). llama_index is written in Python under MIT; lancedb is written in Rust under Apache-2.0. llama_index has attracted 16% as many forks as stars, lancedb 9%. lancedb was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (vector-database), 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
| llama_index | lancedb | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 11K |
| License | MIT | Apache-2.0 |
| Written in | Python | Rust |
| Last push | 2026-09-17 | 2026-09-17 |
| Forks | ⑂ 8.2K | ⑂ 1.1K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama_index if
- You weight community size — 52K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick lancedb if
- You want the lancedb feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Rust
- You evaluated both and lancedb fits your workflow better
About llama_index
LlamaIndex is an MIT licensed, open source Python framework for building agentic applications — retrieval augmented generation systems, agents and multi agent workflows — on top of private documents and data, and it is aimed at AI engineers and teams who need to connect large language models to their own sources of context.
read the full llama_index overview →
About lancedb
LanceDB is an open source, developer friendly embedded retrieval library for multimodal AI, maintained in Rust and released under the Apache 2.0 license. It describes itself as a multimodal AI lakehouse: a single place where developers can build, train and analyze AI workloads over vectors, metadata and multimodal data such as text, images, videos and point clouds. It is built on top of the Lance columnar format, which provides the storage layer for efficient storage and analytics.
read the full lancedb overview →
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Frequently asked questions
Is llama_index or lancedb more popular?
llama_index has 52,202 GitHub stars and lancedb has 11,449. llama_index has the larger community by that measure.
Are llama_index and lancedb free?
Both are open source. llama_index is licensed under MIT and lancedb under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and lancedb?
llama_index is written in Python and lancedb 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, llama_index or lancedb?
Choose llama_index if you want the larger community (52,202 stars) or its MIT licence terms. Choose lancedb if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.