Quantixar: High-performance Vector Data Management System
<|reference_start|>Quantixar: High-performance Vector Data Management System: Traditional database management systems need help efficiently represent and querying the complex, high-dimensional data prevalent in modern applications. Vector databases offer a solution by storing data as numerical vectors within a multi-dimensional space. This enables similarity-based search and analysis, such as image retrieval, recommendation engine generation, and natural language processing. This paper introduces Quantixar, a vector database project designed for efficiency in high-dimensional settings. Quantixar tackles the challenge of managing high-dimensional data by strategically combining advanced indexing and quantization techniques. It employs HNSW indexing for accelerated ANN search. Additionally, Quantixar incorporates binary and product quantization to compress high-dimensional vectors, reducing storage requirements and computational costs during search. The paper delves into Quantixar's architecture, specific implementation, and experimental methodology.<|reference_end|>
@article{yadav2024quantixar:,
    title={Quantixar: High-performance Vector Data Management System},
    author={Gulshan Yadav, RahulKumar Yadav, Mansi Viramgama, Mayank Viramgama,
  Apeksha Mohite},
    journal={arXiv preprint arXiv:2403.12583},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.12583},
    primaryClass={cs.DB}
}