head to head · open source
llama_index vs LongMemory
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. LongMemory has 4,560 stars, 513 forks, 19 open issues and last shipped 16 days ago. llama_index leads on adoption by 1,057% (52,779 vs 4,560 stars). llama_index is written in Python under MIT; LongMemory is written in TypeScript under Apache-2.0. llama_index has attracted 16% as many forks as stars, LongMemory 11%. llama_index was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (llm), 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.
← all 20902 open source comparisons
Side by side
| llama_index | LongMemory | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 4.6K |
| License | MIT | Apache-2.0 |
| Written in | Python | TypeScript |
| Last push | 2026-10-26 | 2026-10-18 |
| Forks | ⑂ 8.5K | ⑂ 513 |
| 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 LongMemory if
- You want the LongMemory feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches TypeScript
- You evaluated both and LongMemory 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 LongMemory
LongMemory Durable, temporal, governed memory for AI agents. Not just RAG. Not just a vector database. Local first and self hosted. LongMemory is a cognitive memory engine for LLM applications and autonomous agents. Durable local first storage with SQLite Immutable content, provenance, and temporal truth Strict, historical, associative, grounded, and multilingual recall Explainable evidence selection and token bounded context Governed project memory, Skills, Chat Memory, LLM Wiki, and CodeGraph One TypeScript engine across npm, CLI, HTTP, MCP, dashboard, and VS Code Native integrations for agent hosts…
read the full LongMemory overview →
More in AI & Machine Learning
Related comparisons
More Machine Learning Infrastructure projects
Compare either of these against the rest of the Machine Learning Infrastructure field.
Frequently asked questions
Is llama_index or LongMemory more popular?
llama_index has 52,779 GitHub stars and LongMemory has 4,560. llama_index has the larger community by that measure.
Are llama_index and LongMemory free?
Both are open source. llama_index is licensed under MIT and LongMemory under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and LongMemory?
llama_index is written in Python and LongMemory in TypeScript. 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 LongMemory?
Choose llama_index if you want the larger community (52,779 stars) or its MIT licence terms. Choose LongMemory if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.