Cognee vs Graphlit
Detailed side-by-side comparison to help you choose the right tool
Cognee
🔴DeveloperAI Knowledge Tools
Cognee is an open-source agent memory platform that builds a hybrid knowledge graph and vector index from your data so LLM agents recall structured facts, not just nearest-neighbour text chunks. Free Hobby, usage-based Growth, custom Enterprise.
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FreeGraphlit
🔴DeveloperKnowledge management
Graphlit review covering ingestion, extraction, search, RAG, MCP access, published pricing, use cases, and the critical wind-down and signup closure.
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💡 Our Take
Choose Cognee if you want open-source, self-hostable, and full control over pipeline internals with no vendor lock-in. Choose Graphlit if you prefer a fully managed commercial platform with built-in connectors, polished APIs, and don't want to operate Neo4j or design your own ontologies — Graphlit trades flexibility for a faster path to production.
Cognee - Pros & Cons
Pros
- ✓Graph + vector hybrid beats vector-only RAG on multi-hop questions
- ✓Pluggable storage — bring your existing Neo4j, pgvector, or Qdrant
- ✓Official MCP server makes Cognee a drop-in memory layer for Claude, Cursor, Goose
- ✓Open-source core means you can self-host and audit the pipeline
- ✓Integrates with LangChain, LlamaIndex, Mastra, and Vercel AI SDK out of the box
Cons
- ✗Graph extraction quality depends on the LLM you run the pipeline with
- ✗Self-host setup is a real ops project vs. dropping in a vector DB
- ✗Overkill for simple FAQ or single-document retrieval
- ✗Managed cloud middle tier ($35–$100/mo) tight for very heavy workloads
Graphlit - Pros & Cons
Pros
- ✓Broad pipeline historically covered ingestion through conversation
- ✓Official page documents limits and credit rates
- ✓MCP access connected context to common clients
Cons
- ✗Graphlit is winding down
- ✗New signups are closed
- ✗Existing customers face migration and export work
- ✗Subscriptions exclude usage credits
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