Comparison
Cognee vs Zep
Cognee and Zep both build agent memory on knowledge graphs, but with different operating models. Cognee is an open-source memory platform you can run fully local or on Cognee Cloud; Zep is a cloud-first context engineering platform built on its temporal knowledge graph, Graphiti.
Based on public information as of June 2026. See each vendor’s site for current details.
At a glance
| Cognee | Zep | |
|---|---|---|
| Open source | Open-source core; the full memory engine runs in your infrastructure | Graphiti, its graph engine, is open source; the platform is cloud-first |
| Graph + vector retrieval | Knowledge graph combined with vector retrieval (“graph memory”) | Temporal knowledge graph built on Graphiti |
| Runs fully local | Fully local or self-hosted; Cognee Cloud is optional | Cloud-first product; the open-source Graphiti engine can be run on its own |
| MCP server | Same memory across Claude Code, Cursor, and other MCP clients | See Zep’s site for current details |
| Managed cloud | Cognee Cloud | Cloud-first platform targeting enterprises; SOC 2 Type II |
| Benchmark claims (attributed) | We publish evaluations on our research page rather than a single headline score | LoCoMo 94.7% with p50 87 ms / p95 155 ms latency, as reported by Zep (May 2026) |
| Best fit | Open-source, graph-structured, self-hostable memory across heterogeneous data | Fully managed context platform with published latency SLOs |
When to choose which
Zep is a strong fit for teams wanting a fully managed context platform with published latency SLOs. It is cloud-first, targets enterprises, holds SOC 2 Type II, and self-reports 94.7% on LoCoMo with p50 87 ms / p95 155 ms latency (May 2026). If you want a vendor to run the context layer for you and commit to latency numbers, that is its pitch.
Cognee is the fit when you want open-source, graph-structured, self-hostable memory across heterogeneous data. The whole engine — not just the graph component — is open source, so memory can run fully local first and the data stays yours. With 28+ data source connectors, a Python SDK (add / cognify / search), and an MCP server that shares one memory across your agents, it runs in production at Bayer, the University of Wyoming, and Knowunity, with 17k+ GitHub stars and 5M+ SDK runs per month.