SingleStoreDB is a database that supports vector data and nearest-neighbor search, enabling powerful query processing in SQL. This allows for applications such as generative AI, chatbots, semantic text search, face matching, and object photo matching to be developed. To get started with using SingleStoreDB for vector search, users can insert vector data into the database using regular INSERT statements or bulk load vectors and associated data using LOAD DATA or PIPELINES. A simple example of loading a data file into the `vectors` table is shown, which demonstrates how to use LOAD DATA and JSON_ARRAY_PACK to convert text-formatted vectors to internal packed binary format required by DOT_PRODUCT and EUCLIDEAN_DISTANCE functions. Users can also validate that vector data is present in the database using SELECT statements with JSON_ARRAY_unpack. For large data sets or continuous streaming loads, users can use PIPELINES instead of LOAD DATA. SingleStoreDB's documentation provides more information on its capabilities for working with vector data, and a free trial is available to get started.