ragflow
★ 92.7k
vs
samyama-graph
★ 184
ragflow vs samyama-graph
ragflow: RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that integrates RAG with Agent capabilities. It provides a superior context layer for LLMs and offers a streamlined RAG workflow adaptable to enterprises of any scale.; samyama-graph: Samyama is a graph-vector database written in Rust. It supports OpenCypher queries, Redis protocol, vector search, and graph algorithms. It can handle billions of edges on a single machine.
01
TL;DR
ragflowRAG / Knowledge Base · ★ 92.7k
When to choose:
- Your documents have complex layouts (PDFs, scanned files, tables, slides) and you need layout analysis, OCR, and traceable citations.
- You want an Apache-2.0 all-in-one RAG platform where you can inspect and hand-tune template-based chunks in a web UI.
When to skip:
- Your server has less than 4 CPU cores and 16 GB RAM; RAGFlow's multi-service stack is heavy.
- You want an autonomous web research agent that writes 2,000-word reports from live search rather than indexing a local document corpus; GPT Researcher fits better.
samyama-graphRAG / Knowledge Base · ★ 184
Biomedical knowledge graphs (PubMed, ClinicalTrials.gov, etc.)
02
Side-by-Side Comparison
Field
ragflowsamyama-graphCategory
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 92.7k
★ 184
License
Apache-2.0
Apache-2.0
Install Command
docker compose -f docker-compose.yml up -d
git clone https://github.com/samyama-ai/samyama-graph && cd samyama-graph && cargo build --release
Updated
1d ago
1d ago
Open Source
Yes
Yes
Tags
RAG, AI Agent, LLM
billion-edges, cypher, cypher-query-language
03
Features
ragflow01Deep document understanding for knowledge extraction from unstructured data.
02Intelligent and template-based chunking with explainable options.
03Grounded citations with reduced hallucinations and traceable references.
04Compatibility with heterogeneous data sources including documents, images, and web pages.
05Automated and effortless RAG workflow orchestration with configurable models and fused re-ranking.
samyama-graph01OpenCypher queries
02Redis protocol
03Vector search (HNSW)
04Graph algorithms (PageRank, BFS, etc.)
05Natural language queries (NLQ)
04
Use Cases
ragflow↳Building high-fidelity, production-ready AI systems with complex data.
↳Developing enterprise-scale knowledge base and intelligent Q&A chatbots.
↳Facilitating intelligent document processing and advanced information retrieval.
samyama-graph↳Biomedical knowledge graphs (PubMed, ClinicalTrials.gov, etc.)
↳Multi-hop graph traversals
↳Cross-knowledge graph aggregation
05
Best For
ragflowMost PopularEssentialTrending
samyama-graph—
FAQ
FAQ
What is the difference between ragflow and samyama-graph?
Both ragflow and samyama-graph are in the RAG / Knowledge Base category. ragflow has 92.7k stars, while samyama-graph has 184 stars.
Which is better, ragflow or samyama-graph?
The best choice depends on your use case. Choose ragflow if Building high-fidelity, production-ready AI systems with complex data., and samyama-graph if Biomedical knowledge graphs (PubMed, ClinicalTrials.gov, etc.).
Is ragflow free or open source?
Yes, ragflow is open source on GitHub (Apache-2.0).
Is samyama-graph free or open source?
Yes, samyama-graph is open source on GitHub (Apache-2.0).
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