SingleStore and TiDB are two popular vector database systems designed to store and query high-dimensional vectors, which encode complex information in AI applications such as e-commerce product recommendations, content discovery platforms, anomaly detection, medical image analysis, and natural language processing. SingleStore is a distributed, relational SQL database management system with built-in in-database vector search capabilities, allowing for efficient similarity matching within the database itself. It supports both exact k-nearest neighbors (kNN) and Approximate Nearest Neighbor (ANN) search methods and can store vector data in columnstore tables. TiDB, on the other hand, is an open-source, distributed SQL database with hybrid transactional and analytical processing capabilities, offering MySQL compatibility and support for external libraries and plugins for vector search. While SingleStore excels at unified vector and relational query at scale, TiDB is well-suited for scenarios requiring HTAP, MySQL compatibility, and custom integrations. The choice between these two systems depends on the specific use case, data types, scalability requirements, and performance needs. Thorough benchmarking with actual datasets and query patterns will be key to making an informed decision.