head to head · open source
llama_index vs knowhere
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. knowhere has 3,882 stars, 337 forks, 40 open issues and last shipped yesterday. llama_index leads on adoption by 1,260% (52,779 vs 3,882 stars). llama_index is written in Python under MIT; knowhere is written in Python under Apache-2.0. llama_index has attracted 16% as many forks as stars, knowhere 9%. knowhere 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 | knowhere | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 3.9K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-10-26 | 2026-11-02 |
| Forks | ⑂ 8.5K | ⑂ 337 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama_index if
- You weight community size — 53K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
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
About llama_index
🗂️ LlamaIndex (OSS Framework) 🦙 [!NOTE] The current focus of LlamaIndex is to build the best AI powered engine for document parsing and extraction. LlamaParse is our enterprise platform for agentic OCR, parsing, extraction, indexing and more. LiteParse represents our efforts to build the best free, fast, cheap text parser in the market. ParseBench and ExtractBench represent our commitment towards open benchmarking for parsing and extraction. The company itself has undergone an evolution since when this OSS framework first launched 3 years ago in 2023. Since the early days, the framework has consisted of a…
read the full llama_index overview →
About knowhere
Prepare unstructured data for AI Agents 🔗 Website 📄 Docs 🏠 Self Host 🖥️ Dashboard Overview Knowhere is a document parsing and retrieval system that turns complex, dirty files into persistent, navigable memory for AI agents—especially across local and offline document collections. It ingests unstructured documents and produces persistent, navigable memory: parsing, hierarchy reconstruction, multi modal structuring, and graph construction in a single pipeline. Every result stays connected to its document, section, source pages, and related assets, making the output a natural fit for Agentic RAG , vector based…
read the full knowhere overview →
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Frequently asked questions
Is llama_index or knowhere more popular?
llama_index has 52,779 GitHub stars and knowhere has 3,882. llama_index has the larger community by that measure.
Are llama_index and knowhere free?
Both are open source. llama_index is licensed under MIT and knowhere under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and knowhere?
llama_index 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, llama_index or knowhere?
Choose llama_index if you want the larger community (52,779 stars) or its MIT licence terms. Choose knowhere if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.