MemMachineLong-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.
Why switchBoth 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.
Full comparison → hindsightAgent memory that learns, not just recalls: retain/recall/reflect API over Postgres, SOTA on LongMemEval. Self-host via Docker with UI; Python/TS clients, any LLM provider.
Why switchSame job — self-hostable agent memory benchmarked on LongMemEval. Hindsight bets on reflect-and-learn over Postgres; Metronix bets on retrieval breadth (dense + sparse + graph). Pick by whether your failure mode is recall or reasoning over what was recalled.
Full comparison → agent-memoryNeo4j Labs' graph-native agent memory: conversations, a POLE+O entity knowledge graph and reasoning traces in one store, with a 16-tool MCP server and hosted or self-hosted backends.
Why switchBoth put agent memory on Neo4j and expose it over MCP. Neo4j Labs' version is graph-purist (POLE+O entities, reasoning traces); Metronix wraps the graph in a hybrid retrieval service with vector and sparse tiers alongside it.
Full comparison → memory-osA 7-layer memory operating system for Hermes Agent: Qdrant vectors, structured facts, fabric recall, an auto-curated wiki, and surgical context injection.
Why switchBoth are layered memory systems built on Qdrant with structured facts alongside vectors. Memory-OS is shaped for the Hermes agent specifically; Metronix targets any MCP-native agent and also ships a native Hermes provider.
Full comparison → omnigraphLakehouse graph database for agent context — graph, vector and full-text retrieval fused in one runtime on branchable Lance/S3 storage; agent fleets write on isolated branches and merge Git-style.
Why switchBoth fuse graph, vector and full-text retrieval into one agent-context runtime. OmniGraph is a lakehouse database with Git-style branch/merge for agent fleets; Metronix is a batteries-included memory service you point an agent at.
Full comparison → utopiaDeepLethe's open 'enterprise world model': one Rust binary plus Postgres running a bitemporal knowledge graph with ontology packs, cited hybrid search, an agent harness and MCP. Air-gap ready.
Why switchBoth put a temporal knowledge graph and an ontology layer under hybrid retrieval, self-hosted. Metronix is memory infrastructure for agents (Postgres + Qdrant + Neo4j in Docker); Utopia is an enterprise knowledge base with a UI, in one Rust binary on Postgres.
Full comparison → LightMemICLR 2026 memory framework for LLMs/agents: LLMLingua pre-compression, topic segmentation and offline memory updates — leading LoCoMo/LongMemEval results at lower token cost.
Why switchBoth attack long-conversation memory quality; metronix ships a Docker stack (Postgres+Qdrant+Neo4j, temporal KG), lightmem is the research framework â compression, topic segmentation, offline updates.
Full comparison →