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Add Zep vs Graphiti comparison table to README (#1014)

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@ -77,6 +77,23 @@ We're excited to open-source Graphiti, believing its potential reaches far beyon
<a href="https://arxiv.org/abs/2501.13956"><img src="images/arxiv-screenshot.png" alt="Zep: A Temporal Knowledge Graph Architecture for Agent Memory" width="700px"></a> <a href="https://arxiv.org/abs/2501.13956"><img src="images/arxiv-screenshot.png" alt="Zep: A Temporal Knowledge Graph Architecture for Agent Memory" width="700px"></a>
</p> </p>
## Zep vs Graphiti
| Aspect | Zep | Graphiti |
|--------|-----|----------|
| **What they are** | Complete managed platform for AI memory | Open-source graph framework |
| **User & conversation management** | Built-in users, threads, and message storage | Build your own |
| **Retrieval & performance** | Pre-configured, production-ready retrieval with sub-200ms performance at scale | Custom implementation required; performance depends on your setup |
| **Developer tools** | Dashboard with graph visualization, debug logs, API logs; SDKs for Python, TypeScript, and Go | Build your own tools |
| **Enterprise features** | SLAs, support, security guarantees | Self-managed |
| **Deployment** | Fully managed or in your cloud | Self-hosted only |
### When to choose which
**Choose Zep** if you want a turnkey, enterprise-grade platform with security, performance, and support baked in.
**Choose Graphiti** if you want a flexible OSS core and you're comfortable building/operating the surrounding system.
## Why Graphiti? ## Why Graphiti?
Traditional RAG approaches often rely on batch processing and static data summarization, making them inefficient for Traditional RAG approaches often rely on batch processing and static data summarization, making them inefficient for