Cognee vs Hyperspell
A side-by-side comparison of Cognee and Hyperspell, two Memory tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Cognee | Hyperspell |
|---|---|---|
| Category | Memory | Memory |
| Pricing (differs) | FREEMIUM | PAID |
| License (differs) | Open core | Proprietary |
| Deployment (differs) | Hybrid | Cloud |
| Platforms | API | API |
| Model support (differs) | BYO key / model | Model-agnostic |
| Vendor (differs) | Cognee | Hyperspell (Digital Workers of California, Inc.) |
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
Hyperspell
Presents connected workspace data as a filesystem agents can mount, instead of making you build retrieval and a vector store yourself.
- 50+ prebuilt workspace connectors
- Filesystem interface works with any agent
- Continuous indexing into a context graph
- SOC 2 and GDPR compliant
- No public pricing listed
- Young, early-stage product
- Cloud-only; data is indexed off-box