MemMachine vs metronix-memory
Long-term memory layer for AI agents — episodic (graph), profile (SQL) and working memory behind Python/TS SDKs, REST and MCP; ships LangChain, LangGraph, CrewAI and LlamaIndex integrations. — versus — Self-hosted agent memory stack in Docker: Postgres + Qdrant + Neo4j hybrid retrieval, a temporal knowledge graph, ontology layer and freshness checks behind one MCP-native API.
Both are long-term memory layers pairing an episodic graph with a profile store behind SDKs and MCP. MemMachine leans on framework integrations (LangChain, CrewAI, LlamaIndex); Metronix ships its own Docker datastores plus an ontology and freshness layer.
| MemMachine | metronix-memory | |
|---|---|---|
| Stars | 3.2k | 95 |
| Forks | 208 | 9 |
| Language | Python | Python |
| License | Apache-2.0 | Apache-2.0 |
| Last activity | today | 3 days ago |
| Topics | memory | memory, rag, knowledge-graphs |
| Curated connections | 14 | 6 |
MemMachine — the curator's take
Pick it when memory is a product requirement, not a cache: separating episodic (graph) from profile (SQL) from working memory maps to how assistants actually personalize, and the documented LangGraph/CrewAI/LlamaIndex integrations mean you don't write the glue. NOT worth the footprint for a single-user tool — it wants a server plus Neo4j and SQL; a vector store or a JSON file gets a prototype further. Watch the open-core boundary: the managed platform is the business model.
metronix-memory — the curator's take
Reach for it when you want one self-hosted box doing dense + sparse + graph retrieval and keeping long-lived facts fresh, and you're willing to run four datastores to get it. Skip it if you only need per-project session recall — a SQLite memory plugin is a fraction of the operational surface. Read the benchmark table with care: they are the author's own N=1 runs under a self-defined protocol, and the honest signal in them is that retrieval scores (Recall@10 85-95%) far outrun end-to-end answers (53-63%) — finding the evidence was never the hard part.