Mem0 Alternative for Agent Memory
Choosing the Right Memory Layer for Your AI Agent

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Personalizing your AI Agent. Which memory layer is suitable for production?
Understand key differences in performance, scalability, security, and enterprise readiness to pick the best long-term memory for your AI Agents.
Zep
Mem0
Proven Retrieval Accuracy (benchmarked)
✅ 94.8% on DMR & 71.2% LongMemEval benchmarks
(Read the paper)
(Read the paper)
❌ No published accuracy benchmarks
Full Temporal Knowledge Graph
✅ Rich temporal context, structured historical data
❌ Limited. Graph capabilities are a bolt-on.
Business Data Integration
✅ Supports business data ingestion & dynamic updates
❌ Limited business data handling, focus on chat history
Low Latency Retrieval (benchmarked)
✅ Benchmarked 90% latency reduction
(Read the paper)
(Read the paper)
✅ Low latency claimed when not using graph. No published benchmarks.
Auditability & Data History Retention
✅ Non-lossy, full historical data retained
⚠️ Partial, focuses on recent interactions
SOC 2 Type 2 Certified & Audited
✅ Certified, Pen-tested
❌ No formal security certifications
Enterprise-Level Scalability
✅ Millions of users; managed or self-hosted deployment
⚠️ No published benchmarks or case studies
SDK and Language Support
Python, TypeScript, Go
Python, TypeScript
Zep is Ready for Enterprise Production and Scale
Effortlessly Scale to Millions of Users and Facts
Zep retrieves user memories instantly, even as your user count and knowledge graph grows.
SOC 2 Type 2 and Privacy Compliance
Be assured with SOC 2 Type II compliance. Zep also offers privacy controls to support CCPA and GDPR compliance.
Powered by Zep's Temporal Knowledge Graph
Zep Integrates With Your Business
Send Zep a stream of chat messages and business data, and it'll intelligently fuse them into a Knowledge Graph—giving your agent accurate, relevant user facts in a single API call.
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Enable Agent Temporal Reasoning
Build Agents That Continuously Learn & Adapt
As users interact with your agent and business, Zep marks outdated facts as invalid, tracks changes, and retains history—enabling agents to reason about evolving user states.
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Framework and Platform Agnostic
Develop agents in Python, TypeScript, or Go - with any framework or none at all.

Python

TypeScript

Go

LangChain
