Cognee vs Graphlit
A side-by-side comparison of Cognee and Graphlit, two Memory tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
The honest brief
Cognee
Builds an LLM-derived knowledge graph alongside embeddings, so recall follows relationships, not just vector similarity.
- Self-hostable Python SDK
- Recall follows concept relationships
- Bring your own LLM/embedding provider
- Newer, smaller ecosystem
- Cognify pipeline adds LLM cost
- Self-host setup overhead
Graphlit
Graph-native context layer that links ingested content into an entity graph plus stateful memory, not just vector chunks.
- One API for ingest, extract, store, retrieve
- Multimodal (docs, audio, video, images)
- Graph-based entity linking + hybrid search
- Event-driven webhooks for reactive agents
- More infra/overhead than plain RAG
- Overkill for simple doc Q&A
- Cloud-only managed service
- Graph/timeline modeling adds complexity