A vector database is specifically designed to store and query high-dimensional vectors, which encode complex information such as semantic meaning of text or visual features of images. Vector databases play a pivotal role in AI applications, enabling efficient similarity searches that allow for advanced data analysis and retrieval. Two popular vector databases are SingleStore and LanceDB. SingleStore is a distributed relational SQL database management system with built-in vector search capabilities, allowing developers to build complex AI applications using standard SQL queries. LanceDB is an open-source serverless vector database designed for multi-modal data, supporting both exhaustive k-nearest neighbors (kNN) search and approximate nearest neighbor (ANN) search. When choosing between SingleStore and LanceDB, consider factors such as the need for dedicated vector search capabilities, scalability requirements, integration with existing databases, ease of use, and cost. Thorough benchmarking with actual datasets and query patterns is essential to make an informed decision.