A1 Journal article (refereed)
Vector database management systems : Fundamental concepts, use-cases, and current challenges (2024)


Taipalus, T. (2024). Vector database management systems : Fundamental concepts, use-cases, and current challenges. Cognitive Systems Research, 85, Article 101216. https://doi.org/10.1016/j.cogsys.2024.101216


JYU authors or editors


Publication details

All authors or editorsTaipalus, Toni

Journal or seriesCognitive Systems Research

ISSN1389-0417

eISSN1389-0417

Publication year2024

Volume85

Article number101216

PublisherElsevier

Publication countryUnited States

Publication languageEnglish

DOIhttps://doi.org/10.1016/j.cogsys.2024.101216

Publication open accessOpenly available

Publication channel open accessPartially open access channel

Publication is parallel published (JYX)https://jyx.jyu.fi/handle/123456789/93620

Web address of parallel published publication (pre-print)https://arxiv.org/abs/2309.11322


Abstract

Vector database management systems have emerged as an important component in modern data management, driven by the growing importance for the need to computationally describe rich data such as texts, images and video in various domains such as recommender systems, similarity search, and chatbots. These data descriptions are captured as numerical vectors that are computationally inexpensive to store and compare. However, the unique characteristics of vectorized data, including high dimensionality and sparsity, demand specialized solutions for efficient storage, retrieval, and processing. This narrative literature review provides an accessible introduction to the fundamental concepts, use-cases, and current challenges associated with vector database management systems, offering an overview for researchers and practitioners seeking to facilitate effective vector data management.


Keywordsvectors (mathematical concepts)databasespropertieschallengesneural networks (information technology)deep learning

Free keywordsvector; database; feature; challenge; neural network; deep learning


Contributing organizations


Ministry reportingYes

Reporting Year2024

Preliminary JUFO rating1


Last updated on 2024-13-05 at 18:06