Vector Search Optimization for Scalable Information Retrieval in Low-Latency Applications

Abstract

In this paper, it is analysed how the modern search systems of vectors are made faster, more accurate and can be easily scaled. It is based on qualitative method in order to review the ideas of research articles, a system within the industry and technical reports. According to the results, it may be reduced with the help of good index structure, adaptive search algorithms and strong design of hardware and software that minimizes the latency and improves the recall. The memory tiering, graph indexes and hybrid search models and their use in supporting large workload e.g. RAG and recommendation are also outlined in the paper. The results show that small contribution of algorithms, memory and hardware in a large number are added to make sure that in real life, the search of vectors is fast and efficient.