Databases designed to store and query high-dimensional vector embeddings for tasks like semantic search and dense retrieval.
More about Vector Databases
Vector Databases are specialized databases optimized for storing and querying vector embeddings. These embeddings represent data such as text, images, or audio in a high-dimensional space, allowing for similarity-based retrieval using metrics like cosine similarity.
Vector databases play a crucial role in systems such as semantic search, dense retrieval, and knowledge retrieval, enabling efficient and accurate retrieval of information in large datasets.
