Venkata Gummadi works on vector search response times:
As data engineers, we are tasked with implementing these sophisticated solutions, ensuring organizations can derive actionable insights from vast datasets. This article explores the intricacies of vector search using Elasticsearch, focusing on effective techniques and best practices to optimize performance. By examining case studies on image retrieval for personalized marketing and text analysis for customer sentiment clustering, we demonstrate how optimizing vector search can lead to improved customer interactions and significant business growth.
Read on for a vector search primer and some guidance of how you can improve the performance of vector search queries. I’d expect that much of this can also apply to Azure AI Search and Amazon OpenSearch.