Graphlit vs Supermemory
A side-by-side comparison of Graphlit and Supermemory, two Memory tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Graphlit | Supermemory |
|---|---|---|
| Category | Memory | Memory |
| Pricing | FREEMIUM | FREEMIUM |
| License (differs) | Proprietary | Open core |
| Deployment (differs) | Cloud | Hybrid |
| Platforms | API, Web | API, Web |
| Model support (differs) | Multi-model | Model-agnostic |
| Vendor (differs) | Graphlit | Supermemory |
| Capabilities (differs) |
|
|
The honest brief
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
Supermemory
MIT-licensed memory engine you self-host or call as a managed API — one recall endpoint across any model.
- MIT-licensed, self-host or managed
- Single recall API across any model
- Connectors: Drive, Gmail, Notion
- Ships MCP server and SDKs
- Younger project, evolving API
- Smaller track record than peers
- Self-hosting needs infra work
When to pick which
Both cover Agent memory, RAG pipeline, Vector search, and Document parsing (structured).
Pick Graphlit if you need Knowledge graph and Transcription (STT).
- Knowledge graph (secondary capability)
- Transcription (STT) (secondary capability)
Pick Supermemory if you need MCP server.
- MCP server (secondary capability)
Graphlit leans on RAG pipeline as a headline capability; Supermemory treats it as secondary.
- RAG pipeline (primary capability)
They also differ on:
- License
- Proprietary · Open core
- Deployment
- Cloud · Hybrid