Memori vs memvid
Persistent AI memory: Memori and memvid compared
Memori and memvid both provide persistent memory for AI applications. Memori focuses on capturing and organizing conversations and agent execution through SDKs and managed or BYODB options, while memvid packages memory and search structures in a portable file for local retrieval.
Memori: Persist Structured Memory for AI Agents
Memori is LLM-agnostic memory infrastructure that turns agent conversations and execution into structured, persistent state. Its Python and TypeScript SDKs support managed cloud, single-tenant cloud, VPC, and on-premises deployments.
memvid: Store Persistent AI Memory in a Single File
Memvid is a Rust-based memory layer that stores content, search indexes, and metadata in a portable .mv2 file. It suits developers building agents that need local, persistent retrieval without operating a separate database service.
| Memori | memvid | |
|---|---|---|
| Language | Python | Rust |
| License | — | Apache-2.0 |
| Stars | 17.2k | 16.6k |
| Forks | 3.8k | 1.4k |
| Last analyzed | Oct 19, 2026 | Oct 3, 2026 |
Key differences
- Memori organizes memory around entities, processes, and sessions; memvid stores content, metadata, and search structures in `.mv2` files.
- Memori offers Python and TypeScript SDKs; memvid offers Rust, Python, and Node.js interfaces, plus a CLI.
- Memori provides managed cloud and BYODB options; memvid is designed for local or offline use without a separate database service.
- Memori includes integrations for agent tools, OpenClaw, Hermes Agent, and compatible MCP clients; memvid offers full-text search, optional vector search, and append-only Smart Frames.
- Memori's repository lists its license as NOASSERTION while its README states Apache 2.0; memvid lists Apache-2.0.
- Memori lists 17.1k stars and 3.6k forks; memvid lists 16.6k stars and 1.4k forks.
Choose Memori if you…
- need structured memory that captures conversations and agent execution across sessions.
- want Python or TypeScript integrations alongside managed cloud or BYODB options.
- need integrations for agent tools, OpenClaw, Hermes Agent, or MCP-compatible clients.
Choose memvid if you…
- want memory and search structures packaged in a portable `.mv2` file.
- need local or offline retrieval without operating a separate database service.
- want Rust, Python, or Node.js interfaces, with optional vector search and encryption capsules.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.