Memori vs ragflow
Side-by-side comparison of two AI agent tools
Short answer
- ragflow is growing faster: +2,402 GitHub stars in the last 30 days vs +370 for Memori.
- Memori is freemium; ragflow is open-source.
- Pick Memori for: lLM-agnostic memory infrastructure that turns agent execution and conversations into persistent state. Pick ragflow for: open-source RAG engine combining knowledge retrieval and agent capabilities for LLMs.
From GitHub data refreshed daily.
M
Memorifreemium
LLM-agnostic memory infrastructure that turns agent execution and conversations into persistent state
ragflowopen-source
Open-source RAG engine combining knowledge retrieval and agent capabilities for LLMs
Metrics
| Memori | ragflow | |
|---|---|---|
| Stars | 17.1k | 91.6k |
| Star velocity /mo | 370 | 2.4k |
| Commits (90d) | 5 | 2.7k |
| Releases (6m) | 10 | 10 |
| Downloads (30d, npm + PyPI) | 19.1K | — |
| Overall score | 0.6281376966364172 | 0.9098521001650974 |
Pros
- +结合了先进的RAG技术和Agent能力,提供比传统RAG更强大的功能
- +开源且拥有活跃社区支持,GitHub星数超过7.6万,可信度高
- +提供云服务和Docker容器化部署,支持多种部署方式
Cons
- -作为相对复杂的RAG系统,可能需要一定的技术背景才能充分配置和优化
- -大规模部署可能需要相当的计算资源和存储空间
Use Cases
- •企业知识库问答系统,基于内部文档为员工提供智能查询服务
- •智能客服系统,结合产品文档和FAQ提供准确的客户支持
- •研究助手应用,帮助研究人员从大量学术文献中检索相关信息
FAQ
- Which is more popular, Memori or ragflow?
- ragflow has more GitHub stars (91,619 vs 17,064).
- Which is more actively developed, Memori or ragflow?
- ragflow had more commits in the last 90 days (2,666 vs 5).
- Should I use Memori or ragflow?
- Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.