Cognee vs. Supermemory

Memory your agents own and reason on.

Supermemory is built for conversational recall: plug-and-play, with a broad set of connectors. Cognee is a self-evolving memory engine that reasons: it auto-generates ontologies and gets more useful every time your agents reuse it. Your agents will start learning from their mistakes.

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Key takeaways

What sets cognee apart.

Self-evolving

Supermemory is a good fit when the job is remembering what was said and surfacing it quickly. With Cognee, every correction and action feeds back, so cognee's memory gets more useful the more your agents work with it. The result is fewer agent mistakes.

Customizable to your domain

Cognee auto-generates ontologies and supports custom data schemas, so your memory mirrors your domain instead of a generic chunk index.

One Postgres, no graph database

Cognee runs the entire layer on a single Postgres instance you already operate. There is no separate vector or graph service to set up and maintain.

Yours to keep

Cognee is open source (Apache 2.0), and your memory is exportable at any time via open COGX or standard graph formats. Supermemory operates a managed cloud with an open core (MIT).

The distinction

Supermemory remembers.Cognee remembers and improves.

What Supermemory is

Plug-and-play conversational memory

For an agent that only needs to recall a conversation, Supermemory works. Supermemory is built for conversational recall: plug-and-play, with a broad set of connectors around a dedicated vector store. It is a good fit when the job is remembering what was said and surfacing it.

What cognee is

Memory that evolves and is yours

Cognee is built for teams whose agents need to reason over memory, beyond simple recall. We built a memory layer many agents read from and write back to. It auto-generates ontologies and supports custom schemas, so your memory mirrors your domain instead of a generic chunk index. It is self-evolving: every correction and reuse feeds back. When many agents share one knowledge layer and learn across it, cognee fits best.

Side by side

Cognee vs. Supermemory at a glance.

Memory model
Supermemory

Managed memory on a vector-graph engine

Cognee

Self-evolving memory that curates itself

Graph + vector retrieval
Supermemory

Hybrid retrieval with vector similarity and graph traversal

Cognee

Hybrid search with no separate index to build or keep in sync

Infrastructure
Supermemory

A proprietary engine with internals not disclosed

Cognee

A single Postgres for graph, vectors, sessions, and metadata

Deployment
Supermemory

Managed cloud or self-hosted binary

Cognee

Local, managed cloud, or on the edge

Open source
Supermemory

Open core (MIT)

Cognee

Open source (Apache 2.0), with memory you can export anytime via open COGX

Best for
Supermemory

Conversational recall and per-user personalization

Cognee

From agent personalization to multi-agent environments on one shared memory

Benchmarks

How we measure memory.

Supermemory measures retrieval recall and token efficiency: how few tokens it takes to find the right memories. Cognee evaluates on BEAM, a long-horizon benchmark that measures reasoning accuracy across many turns.

Supermemory — LongMemEval
Recall@15 accuracy0%
Mean tokens @15~0
Context reduction @150.0%
Multi-session recall0%
Cognee — BEAM
BEAM 100K accuracy0%
vs. previous SOTA+0%
BEAM 10M accuracy0%
Human-like correctness (CoT)0.0%

Supermemory measures Recall@k on LongMemEval, optimising for how few tokens are needed to retrieve the right memories. Cognee is evaluated on BEAM, a long-horizon benchmark measuring reasoning accuracy when evidence is scattered across many turns. Full methodology and reproducible benchmark code are publicly available.

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