OMEGA vs Zep
Zep (and its open-source engine Graphiti) builds a temporal knowledge graph on Neo4j. OMEGA takes a lighter approach: local SQLite, zero external dependencies, and 24 points higher on LongMemEval.
Graph-native vs graph-augmented. Two architectures for structured agent memory.
The Key Difference
Local-first intelligence layer
A standalone memory server with built-in graph relationships, running on SQLite. No Neo4j, no Docker, no external databases. Adds memory, coordination, and learning to any MCP client. All on your machine.
Temporal knowledge graph
A graph-native memory system built on Neo4j with strong temporal reasoning. Bi-temporal model tracks when facts were true and when they were recorded. Requires Neo4j 5.26+ as an external dependency.
Full Comparison
Every row verified from public documentation and GitHub repos. Updated March 2026.
Which Should You Use?
Use OMEGA if you…
- ✓Want zero external dependencies (no Neo4j, no Docker)
- ✓Benchmark performance matters (95.4% vs 71.2% on LongMemEval)
- ✓Use Claude Code, Cursor, or Windsurf and want memory via MCP
- ✓Want a single pip install, not a multi-service deployment
- ✓Need checkpoint/resume for long-running tasks
- ✓Want intelligent forgetting with audit trails
Use Zep if you…
- ✓Temporal reasoning is your primary use case (bi-temporal model is excellent)
- ✓You already run Neo4j in your infrastructure
- ✓You want a managed cloud platform (Zep Cloud)
- ✓You need deep graph traversal capabilities beyond what OMEGA offers
- ✓You are building conversational agents that need episode-level memory
All data verified March 2026 from official documentation and public GitHub repositories. OMEGA's LongMemEval score uses the standard methodology (Wang et al., ICLR 2025). Zep's 71.2% score is self-reported from their blog post.