How does a vector database work? | Algolia

Vector databases are an emerging technology that store, process, and analyze data sequences in a way that machines can easily understand. They represent information as vectors, which are numerical representations of words or vector embeddings. These databases are ideal for tasks involving natural language processing (NLP) and recognizing the content of images. Vector databases can accommodate large datasets and have become popular due to their ability to enhance user search and discovery. They work by generating embeddings from content, indexing them using algorithms, and querying them to retrieve relevant information quickly. In enterprise search frameworks, vector search powered by artificial intelligence enables more accurate search, on-point recommendation systems, and prediction of desired content even with large datasets.