📖 The AI Tool Bible

Cognee vs Weaviate

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

 
Cognee
RAG
Weaviate
RAG
TaglineOpen-source graph-memory layer that gives AI agents persistent, queryable context across sessions.Open-source vector DB with hybrid search and modules.
CategoryRAGRAG
PricingFreemium· Hobby free (1M tokens/mo); Growth $5/workspace/mo + token usage; Enterprise customFreemium· Free open-source; cloud from $25/mo
ModelMulti-model (Claude, OpenAI, others)Hosted vector DB (not an LLM)
Editorial score—8.4 / 10
Use cases
agent-memoryknowledge-graphsragmulti-agent-systemssecond-braincontext-retrieval
self-hosted RAGhybrid search
Pros
  • Open source and self-hostable with a sizable GitHub community
  • Graph-based memory beats flat vector RAG for entity-heavy domains
  • MCP server makes it easy to plug into Claude Desktop and agent frameworks
  • Generous free tier (1M tokens/month) for experimentation
  • Adapters for warehouses, docs, chats, and APIs out of the box
  • Hybrid search built in
  • Self-host or cloud
  • Module ecosystem
  • GraphQL + REST APIs
Cons
  • Graph memory adds operational complexity vs. a plain vector store
  • Still a young product; ontologies and governance features are evolving
  • Token-based pricing on top of LLM costs can compound at scale
  • More ops than Pinecone if self-hosted
  • Smaller community
Websitewww.cognee.aiweaviate.io
Pick Cognee if
  • ✅ Open source and self-hostable with a sizable GitHub community
  • ✅ Graph-based memory beats flat vector RAG for entity-heavy domains
  • ✅ MCP server makes it easy to plug into Claude Desktop and agent frameworks
  • ✅ Generous free tier (1M tokens/month) for experimentation
Pick Weaviate if
  • ✅ Hybrid search built in
  • ✅ Self-host or cloud
  • ✅ Module ecosystem
  • ✅ GraphQL + REST APIs
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