Chroma vs memvid
Open-source embedding database for building AI apps with retrieval. — versus — Single-file memory layer for agents: data, embeddings, index and metadata in one portable .mv2 — append-only Smart Frames, time-travel queries, sub-5ms recall, no server. Rust core, Node/Python SDKs.
Opposite infrastructure bets for agent recall: Chroma is a serverful embedding database you run and query; memvid packs data, embeddings and index into a single file the agent carries — no server, no pipeline.
| Chroma | memvid | |
|---|---|---|
| Stars | 29k | 16k |
| Forks | 2.4k | 1.4k |
| Language | Python | Rust |
| License | Apache-2.0 | Apache-2.0 |
| Last activity | 3 days ago | 14 days ago |
| Topics | rag, memory | memory, local |
| Curated connections | 10 | 2 |
Chroma — the curator's take
Open-source embedding database for building AI apps with retrieval.
memvid — the curator's take
The portability bet is the real differentiator: one .mv2 capsule holds the whole memory — hand it to another agent, ship it offline, branch it, rewind it. The project began life literally encoding text into video frames; the codec DNA survived the Rust rewrite as compression smarts, and the maturity question survives with it. Benchmark claims (+35% SOTA on LoCoMo, '1,372× throughput') are self-run — the eval is open, so run it before repeating it. When NOT: team-shared concurrent memory — single file, append-only, no server means no multi-writer story; that's what the server-based layers are for.