SingleStoreDB is a real-time, distributed SQL database that can supercharge apps with AI-powered semantic search capabilities. It supports fast writes and efficient querying, making it ideal for managing large-scale transactional workloads and delivering real-time analytics. SingleStoreDB's patented Universal Storage supports both OLTP and OLAP workloads, making it suitable for semantic search use cases. The database provides vector database extensions, including built-in functions for vector similarity calculations such as cosine similarity and Euclidean distance. These functions can be leveraged in SQL queries to perform similarity calculations efficiently on large volumes of vector data. SingleStoreDB's distributed architecture and efficient low-level execution enable fast and efficient vector similarity matching without the need for parallelizing the application or moving data from the database into the application. The database provides a familiar and powerful interface for building semantic search applications through its support for SQL. SingleStoreDB allows developers to update and query vector data in real-time, enabling continuous learning and adaptation of applications, providing users with increasingly precise and tailored responses over time.