VectrixDB-package: VectrixDB: Lightweight Vector Database with Embedded Machine...

In VectrixDB: Lightweight Vector Database with Embedded Machine Learning Models

VectrixDB: Lightweight Vector Database with Embedded Machine Learning Models

Description

A lightweight vector database for text retrieval in R with embedded machine learning models and no external API (Application Programming Interface) keys. Supports dense and hybrid search, optional HNSW (Hierarchical Navigable Small World) approximate nearest-neighbor indexing, faceted filters with ACL (Access Control List) metadata, command-line tools, and a local dashboard built with 'shiny'.

VectrixDB is a lightweight vector database with embedded machine learning models that do not require external API (application programming interface) keys. It supports dense, hybrid, and graph-based search modes and includes a built-in dashboard.

Main Functions

• Vectrix - Simple API for text-in, results-out workflow

• VectrixDB - Advanced database interface

• Collection - Vector collection management

• vectrix_serve - Start REST API server

Search Modes

• dense - Semantic vector search

• sparse - BM25 keyword search

• hybrid - Combined dense + sparse

• ultimate - Full pipeline with reranking

• neural - ColBERT + cross-encoder

Author(s)

Maintainer: Kwadwo Daddy Nyame Owusu Boakye [e-mail]

See Also

Useful links:

• https://knowusuboaky.github.io/vectrixdb-r/

• https://github.com/knowusuboaky/vectrixdb-r

• Report bugs at https://github.com/knowusuboaky/vectrixdb-r/issues

Examples

## Not run: 
# Simple usage
db <- Vectrix$new("my_docs")
db$add(c("Python is great", "R is awesome", "Julia is fast"))
results <- db$search("programming language")
print(results$top()$text)

## End(Not run)

VectrixDB documentation built on Feb. 20, 2026, 5:09 p.m.