# ruvnet/RuVector

RuVector is a High Performance, Real-Time, Self-Learning Ai, Vector GNN, Memory DB built in Rust.

Repository: https://github.com/ruvnet/RuVector
Canonical: https://ross.abutalabs.com/products/ruvector
Homepage: https://Cognitum.One/RuVector
Language: Rust
License: MIT
License Family: permissive
Topics: ai, ai-ocr, gnn, graph, llm-inference, low-latency, neo4j, ocr, onnx, rust, vector, wasm, attention-mechanism, gnn-model, gnns, graph-neural-networks, mincut
Last push: 2026-08-26T07:36:21+00:00

## Health v2 (maintenance only)
Score: 82/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 95, longevity 20
- inputs: {"age_days": 287, "days_push": 7, "days_rel": 35, "gap_med": 2.0, "n_releases_24m": 43}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4456, forks 589 (observed 2026-08-28T04:08:50.588641+00:00)

## What it is
RuVector is a Rust-native vector database and memory substrate for AI agents, combining persistent semantic embeddings, graph relationships, and feedback-based learning. It ships as a Rust crate and an npm package with a CLI for storing and recalling agent memories locally without a database server.

## Use cases
- give ai agents persistent memory across sessions
- store and recall semantic memories locally
- build a vector database in rust
- add graph relationships to vector retrieval
- run local embeddings without an api key
- record feedback so agent memory improves over time

## When to choose
- you need persistent, self-learning memory for AI agents with local-first storage
- you want a high-performance Rust vector database with graph and GNN features
- you need semantic recall without running a database server or external API

## When to avoid
- you need a battle-tested, widely adopted vector database like pgvector or Qdrant for production workloads
- you require multi-model or multi-dimension embedding stores without reembedding
- you need managed hosting and a mature ecosystem around your vector store

## Facets
- artifact type: library
- maturity: active
- function: vector-database, rag, machine-learning, database, search-engine, cli
- domain: databases, artificial-intelligence, developer-tools
- platform: rust, cli, cross-platform, wasm
- tags: agent-memory, embeddings, graph-neural-networks, onnx, persistent-memory, self-learning, low-latency, ai-agents, retrieval-augmented-generation, nodejs

## Member repositories
- ruvnet/RuVector (main) score 82

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:50.588641+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:20:44.519933+00:00, confidence not recorded.
  - readme: https://github.com/ruvnet/RuVector (fetched 2026-08-28T04:08:50.588641+00:00, sha 414d110bf00e)
  - homepage: https://Cognitum.One/RuVector (fetched 2026-08-29T09:07:34.400633+00:00, sha 56c3cb3abc93)
- Data as of 2026-08-30T08:39:29.467469+00:00.