Zep vs Cognee

Detailed side-by-side comparison to help you choose the right tool

Zep

🔴Developer

AI Knowledge Tools

Enterprise agent memory built on temporal Context Graphs (Graphiti) with millisecond retrieval, SOC 2 Type II, and HIPAA BAA.

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Starting Price

Free

Cognee

🔴Developer

AI Knowledge Tools

Cognee is an open-source agent memory platform that builds a hybrid knowledge graph and vector index from your data so LLM agents recall structured facts, not just nearest-neighbour text chunks. Free Hobby, usage-based Growth, custom Enterprise.

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Starting Price

Free

Feature Comparison

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FeatureZepCognee
CategoryAI Knowledge ToolsAI Knowledge Tools
Pricing Plans408 tiers8 tiers
Starting PriceFreeFree
Key Features
  • Temporal Knowledge Graph
  • Context Engineering
  • Graph RAG
  • Workflow Runtime
  • Tool and API Connectivity
  • State and Context Handling

Zep - Pros & Cons

Pros

  • Temporal knowledge graph captures when facts changed — better than "last-message wins" vector memory
  • ~200ms retrieval keeps memory viable in latency-sensitive agent flows
  • Credit-based pricing makes storage and retrieval free — predictable for read-heavy agents
  • SOC 2 Type II + HIPAA BAA + DPA make procurement realistic at regulated enterprises
  • First-class MCP server integrates with Claude Desktop, Cursor, and OpenAI Agents SDK out of the box

Cons

  • Credit math (1 credit per 350 bytes per Episode) is hard to forecast until you measure real payloads
  • Free tier (1,000 credits/mo, no rollover) is tight even for evaluation
  • Webhooks, analytics, and custom extraction live only on Flex Plus ($375/mo) and above
  • Most compliance value (audit retention, BYOK/BYOC) is gated behind Enterprise pricing
  • Temporal graph modeling adds upfront design work vs throwing chat history into a vector DB

Cognee - Pros & Cons

Pros

  • Graph + vector hybrid beats vector-only RAG on multi-hop questions
  • Pluggable storage — bring your existing Neo4j, pgvector, or Qdrant
  • Official MCP server makes Cognee a drop-in memory layer for Claude, Cursor, Goose
  • Open-source core means you can self-host and audit the pipeline
  • Integrates with LangChain, LlamaIndex, Mastra, and Vercel AI SDK out of the box

Cons

  • Graph extraction quality depends on the LLM you run the pipeline with
  • Self-host setup is a real ops project vs. dropping in a vector DB
  • Overkill for simple FAQ or single-document retrieval
  • Managed cloud middle tier ($35–$100/mo) tight for very heavy workloads

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🔒 Security & Compliance Comparison

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Security FeatureZepCognee
SOC2
GDPR
HIPAA
SSO
Self-Hosted✅ Yes
On-Prem✅ Yes✅ Yes
RBAC
Audit Log
Open Source✅ Yes
API Key Auth✅ Yes✅ Yes
Encryption at Rest✅ Yes
Encryption in Transit✅ Yes✅ Yes
Data Residencyconfigurable
Data Retentionconfigurableconfigurable
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