The database market is seeing a proliferation of specialty vector databases that promise to solve specific problems with querying for vector similarity. However, these products often lead to redundant data, excessive data movement, and other issues due to their limited capabilities. Instead of relying on these specialty vector databases, developers can build their applications on general, modern data platforms like SingleStoreDB, which supports multiple data models and provides a powerful vector database subsystem with fast nearest-neighbor search and metadata filtering capabilities. SingleStoreDB excels at vector-based operations and is truly a modern database management system with benefits such as ANSI SQL, ACID transactions, high availability, and programmability. The platform's support for vectors and vector similarity search using dot_product and euclidean_distance functions enables applications like face recognition, visual product photo search, and text-based semantic search. With SingleStoreDB, developers can easily build their applications on a scalable, modern data platform that meets all their database requirements, not just one.