Head-to-head · AI Agent Memory Tools
Cognee vs Engrama
Cognee leads on 0 checks, Engrama on 0, and 4 are even. Who comes out ahead on the 4 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.
Our verdict
- Highest scoreCognee · 7.7/10
- Free planboth
Cognee scores higher on our rubric for ai agent memory tools: 7.7 against 7.5 out of 10; our editors rank them #5 and #7.
Cognee is the better fit for teams building knowledge-graph agent memory. Engrama is the better fit for developers wanting graph memory with profiles.
- Cognee fits best
Teams building knowledge-graph agent memory
- Engrama fits best
Developers wanting graph memory with profiles
Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. How we rank.
Side by side
| Feature | Cognee 7.7/10 Visit ↗ | Engrama 7.5/10 Visit ↗ |
|---|---|---|
| At a glance | ||
| Editor score | 7.7 | 7.5 |
| Ranking | #5 in AI Agent Memory Tools | #7 in AI Agent Memory Tools |
| Best for | Teams building knowledge-graph agent memory | Developers wanting graph memory with profiles |
| Pricing model | Free plan + paid | Free plan + paid |
| Starting price | $1/unit usage-based | $19/mo |
| Free plan | ✓ | ✓ |
| Free trial | — | — |
| Deployment | Cloud, Self-hosted | Cloud, Self-hosted |
| Platforms | Web | Web |
| Support | Email, Community, Docs | Community |
| Integrations | 7 integrations | 8 integrations |
| Built for | Solo, Small business, Mid-market, Enterprise | Small business, Mid-market, Enterprise |
| Features Cognee 3/4 · Engrama 3/4 | ||
| Semantic memory | ✓ | ✓ |
| Episodic memory | Not checked yet | Not checked yet |
| User/profile memory | ✓ | ✓ |
| Graph-based memory | ✓ | ✓ |
| Specs | ||
| Deployment options | Both | Both |
| SDK languages | Not checked yet | 2 |
| Retention policy | Not checked yet | Not checked yet |
| Our review | ||
| Pros |
|
|
| Cons |
|
|
| Our verdict | Cognee is an open-source memory engine and knowledge-graph platform for developers building AI agents and other AI applications. It ingests text, documents, and structured data, then processes them into graphs with entities, relationships,… Read the review → |
Engrama provides long-term memory infrastructure for AI agents, copilots, chatbots and personal assistants. It extracts facts and intents from conversations and connected data, links them in typed, versioned graphs, and returns ranked… Read the review → |
Strengths and trade-offs
Cognee — where it wins
- Transforms varied data into searchable entities-and-relationships graphs
- Supports natural-language, temporal, completion, and chunk searches
- Offers open-source self-hosting plus managed Cognee Cloud
Where it doesn't
- Usage-based billing can make monthly costs harder to forecast
- BYOC and dedicated support are available only on Enterprise
- Graph-centered workflows may exceed the needs of simple memory stores
Engrama — where it wins
- Automatic fact and intent extraction from conversations
- Typed, versioned graphs with hybrid graph and vector retrieval
- Hosted or self-hosted deployment with TypeScript and Python SDKs
Where it doesn't
- Analytics and webhooks are available only on paid tiers
- SSO/SAML and uptime SLAs start with the Scale plan
- Unlimited tokens and search are reserved for Enterprise
- Cognee7.7/10 · Free plan
Graph-based agent memory with cloud or self-hosted deployment and usage pricing.
Visit CogneeFull verdict → - Engrama7.5/10 · Free plan
Engrama gives agents graph-based memory, profiles and hybrid retrieval from $19 monthly.
Visit EngramaFull verdict →
More comparisons
- Cloudflare Agent Memory vs Cognee
- Cloudflare Agent Memory vs Engrama
- Mem0 vs Cognee
- Mem0 vs Engrama
- MCP Memory Service vs Cognee
- MCP Memory Service vs Engrama
- Hindsight vs Cognee
- Hindsight vs Engrama
All AI agent memory tools comparisons → · Full ranking →
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Last updated · How we research and update