📖 The AI Tool Bible

OneKE vs Weaviate

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

 
OneKE
RAG
Weaviate
RAG
TaglineOpen-source multi-agent framework for schema-guided knowledge extraction from documents.Open-source vector DB with hybrid search and modules.
CategoryRAGRAG
PricingFree· Free, MIT-licensed; you pay for LLM API calls or self-hosted computeFreemium· Free open-source; cloud from $25/mo
ModelMulti-model (OneKE-13B, LLaMA3, Qwen2.5, GPT, DeepSeek-R1)Hosted vector DB (not an LLM)
Editorial score—8.4 / 10
Use cases
knowledge-graph-constructionnamed-entity-recognitionrelation-extractionevent-extractiondocument-parsing
self-hosted RAGhybrid search
Pros
  • Covers NER, RE, EE, and triple extraction in one framework
  • Works with API models or fully local LLMs via vLLM
  • Ingests PDF, Word, HTML, JSON, and plain text out of the box
  • Multi-agent schema + reflection loop improves extraction quality
  • MIT license with Docker and Streamlit UI included
  • Hybrid search built in
  • Self-host or cloud
  • Module ecosystem
  • GraphQL + REST APIs
Cons
  • Documentation is primarily Chinese and scattered across Yuque/GitHub
  • Self-hosting and tuning agents is non-trivial for non-researchers
  • No managed cloud offering; you bring the infrastructure
  • Quality depends heavily on the underlying LLM you wire in
  • More ops than Pinecone if self-hosted
  • Smaller community
Websiteopenspg.yuque.comweaviate.io
Pick OneKE if
  • ✅ Covers NER, RE, EE, and triple extraction in one framework
  • ✅ Works with API models or fully local LLMs via vLLM
  • ✅ Ingests PDF, Word, HTML, JSON, and plain text out of the box
  • ✅ Multi-agent schema + reflection loop improves extraction quality
Pick Weaviate if
  • ✅ Hybrid search built in
  • ✅ Self-host or cloud
  • ✅ Module ecosystem
  • ✅ GraphQL + REST APIs
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