Cognee vs Memori
A side-by-side comparison of Cognee and Memori, 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
Memori
Stores agent memory in ordinary SQL (Postgres/MySQL/SQLite) with one line of code — no separate vector database to run or pay for.
- Persistent memory in standard SQL databases
- LLM-agnostic; bring any provider key
- No vendor lock-in; data stays in your DB
- Dual-mode working + long-term recall
- Younger than Mem0/Zep, smaller ecosystem
- SQL-first design may not suit graph use cases
- Self-hosting means you run the database