Cognee vs MemMachine
A side-by-side comparison of Cognee and MemMachine, two Memory tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Cognee | MemMachine |
|---|---|---|
| Category | Memory | Memory |
| Pricing (differs) | FREEMIUM | FREE |
| License (differs) | Open core | Open source |
| Deployment (differs) | Hybrid | Self-host |
| Platforms (differs) | API | API, CLI |
| Model support (differs) | BYO key / model | Model-agnostic |
| Vendor (differs) | Cognee | MemMachine |
| Capabilities (differs) |
|
|
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
MemMachine
Pairs episodic (conversational) and profile (long-term user-fact) memory in one model-agnostic, self-hostable layer.
- Fully open source (Apache-2.0)
- Recall persists across sessions
- Model-agnostic across providers
- Self-hostable, Python-first
- Younger than Mem0/Zep
- Self-hosting and ops on you
- Managed enterprise tier not yet GA
When to pick which
Across the signals we compare, Cognee and MemMachine differ on pricing, license, deployment, and platforms:
- Pricing
- FREEMIUM · FREE
- License
- Open core · Open source
- Deployment
- Hybrid · Self-host
- Platforms
- API · API, CLI
Their capability lists differ in recorded depth — compare the full lists above before deciding.