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 editors: Taipalus, Toni
Journal or series: Cognitive Systems Research
ISSN: 1389-0417
eISSN: 1389-0417
Publication year: 2024
Volume: 85
Article number: 101216
Publisher: Elsevier
Publication country: United States
Publication language: English
DOI: https://doi.org/10.1016/j.cogsys.2024.101216
Publication open access: Openly available
Publication channel open access: Partially 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.
Keywords: vectors (mathematical concepts); databases; properties; challenges; neural networks (information technology); deep learning
Free keywords: vector; database; feature; challenge; neural network; deep learning
Contributing organizations
Ministry reporting: Yes
VIRTA submission year: 2024
Preliminary JUFO rating: 1
