VectrixDB: Lightweight Vector Database with Embedded Machine Learning
Models
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'. The HNSW method is
described by Malkov and Yashunin (2018) <doi:10.1109/TPAMI.2018.2889473>.
| Version: |
1.1.2 |
| Imports: |
R6, jsonlite, digest, Matrix, text2vec (≥ 0.6.0), stopwords, tools, utils, stats, RSQLite, DBI |
| Suggests: |
testthat (≥ 3.0.0), shiny, plumber, pkgdown, RcppAnnoy, reticulate, rappdirs |
| Published: |
2026-02-20 |
| DOI: |
10.32614/CRAN.package.VectrixDB (may not be active yet) |
| Author: |
Kwadwo Daddy Nyame Owusu Boakye [aut, cre] |
| Maintainer: |
Kwadwo Daddy Nyame Owusu Boakye <kwadwo.owusuboakye at outlook.com> |
| BugReports: |
https://github.com/knowusuboaky/vectrixdb-r/issues |
| License: |
Apache License (≥ 2) |
| URL: |
https://knowusuboaky.github.io/vectrixdb-r/,
https://github.com/knowusuboaky/vectrixdb-r |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
VectrixDB results |
Documentation:
Downloads:
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