[2310.11703] A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challenge

Computer Science > Databases arXiv:2310.11703 (cs) [Submitted on 18 Oct 2023 (v1), last revised 20 Mar 2026 (this version, v3)] Title:A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challenge Authors:Le Ma, Ran Zhang, Yikun Han, Shirui Yu, Zaitian Wang, Zhiyuan Ning, Jinghan Zhang, Ping Xu, Pengjiang Li, Wei Ju, Chong Chen, Dongjie Wang, Kunpeng Liu, Pengyang Wang, Pengfei Wang, Yanjie Fu, Chunjiang Liu, Yuanchun Zhou, Chang-Tien Lu View a PDF of the paper titled A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challenge, by Le Ma and 18 other authors View PDF HTML (experimental) Abstract:As high-dimensional vector data increasingly surpasses the processing capabilities of traditional database management systems, Vector Databases (VDBs) have emerged and become tightly integrated with large language models, being widely applied in modern artificial intelligence systems. However, existing research has primarily focused on underlying technologies such as approximate nearest neighbor search, with relatively few studies providing a systematic architectural-level review of VDBs or analyzing how these core technologies collectively support the overall capacity of VDBs. This survey aims to offer a comprehensive overview of the core designs and algorithms of VDBs, establishing a holistic understanding of this rapidly evolving field. First, we systematically review the key technologies and design principles of VDBs from the two ...