EverOSOne portable memory layer for every agent: conversations, files and trajectories kept as canonical Markdown, indexed locally by SQLite and LanceDB, with offline reflection that refines them.
Why switchBoth unify memory, files and skills into one human-readable store rather than an opaque index. OpenViking runs a `viking://` filesystem with L0/L1/L2 tiers and traceable retrieval; EverOS keeps plain Markdown as truth with local indexes and offline reflection. Filesystem metaphor versus editable files.
Full comparison → MemOSMemTensor's memory OS for LLM agents: one API over graph-structured, multi-modal memory with hybrid retrieval and skill evolution — hosted, self-hosted (Neo4j + Qdrant) or local plugins.
Why switchBoth unify memories, resources and skills for agents and distill sessions into long-term memory. OpenViking exposes it as a viking:// filesystem; MemOS as a graph-structured memory API.
Full comparison → 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 backends for agents; MemMachine exposes episodic, profile and working memory through SDKs, OpenViking makes the entire context a browsable namespace with tiered summaries. Pick by whether you want an API or a filesystem agents explore.
Full comparison → AcontextSkill memory layer for agents: auto-captures learnings from runs into plain Markdown skill files you can read, edit, git and share across frameworks — memory without an opaque store.
Why switchShared premise — agent memory should be inspectable artifacts, not an opaque store. acontext keeps it as plain Markdown skill files in git; OpenViking runs a server with semantic tiering and vector-guided directory retrieval. acontext for git-native simplicity, OpenViking for scale and traceable recall.
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 switchTwo substrates for agent context: Neo4j Labs' POLE+O entity graph behind a 16-tool MCP server, versus Volcengine's viking:// filesystem an agent can ls, tree and grep. Graph semantics vs shell-native familiarity.
Full comparison → ChromaOpen-source embedding database for building AI apps with retrieval.
Why switchOpenViking is explicitly a reaction to querying a black-box vector store: Chroma hands you the embedding index as a library primitive, OpenViking layers an opinionated filesystem, tiering and session distillation on top. Take Chroma when you want to design retrieval yourself.
Full comparison →