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Memorg vs Mem0
LLM-extracted memory · managed + OSS
Mem0 is the best-known competitor in this space. It pitches a smart memory pipeline driven by an LLM extractor. Memorg is the opposite design: deterministic ranking, local file, smaller surface.
| Feature | Memorg | Mem0 | Advantage |
|---|---|---|---|
| Primary form factor | Python library + MCP server | Hosted API + open-source SDK | Comparable |
| Storage model | Hierarchical: session/conversation/topic/exchange in SQLite | Extracted-fact memories in a vector store (+ optional graph) | Comparable |
| Write-path LLM call | No — exchanges are stored as-is and embedded | Yes — an LLM extracts atomic facts to memorise | Memorg |
| Vector index | USearch, in-file alongside SQLite | Pluggable: Qdrant, Pinecone, pgvector, others | Mem0 |
| Default deployment | Local — one process, one file | Hosted (mem0.ai) or self-host | Comparable |
| Retrieval ranking | Deterministic blend: semantic + recency + importance | Vector similarity over extracted facts | Memorg |
| Token-budget aware | Yes — fits results to a session-level token budget | Configurable on the client | Comparable |
| MCP server | Ships with the package (memorg-mcp / FastMCP) | Community / not first-party | Memorg |
| Maturity | Alpha on PyPI, MIT | Production users, Apache-2.0 | Mem0 |
| License | MIT | Apache-2.0 | Comparable |
Pick Memorg when
- ▸You want a small, deterministic library that runs in your process with no managed service
- ▸You prefer a relational hierarchy (session → conversation → topic → exchange) over an extracted-fact stream
- ▸You want a single SQLite file you can copy, version, and back up
- ▸You already have an agent loop and only want the memory layer, not a memory product
Pick Mem0 when
- ▸You want a hosted offering with a control plane and per-user isolation out of the box
- ▸You want LLM-driven fact extraction baked into the write path
- ▸You need a graph store for entity-relationship recall today
- ▸You prefer adapters for multiple vector DBs and embedding providers in the same library
Still deciding?
Most teams end up running both kinds of system in different parts of their stack. Try Memorg where the answer is "I just need recall over a session," and keep Mem0 where you need the rest of its surface.