Vector Database
A vector database is a database specialized in storing and quickly retrieving the mathematical vectors (strings of numbers) generated by AI models to represent the meaning of data.
How it works
It works by calculating the similarity between vectors (for example, texts with similar meanings have similar vectors), enabling semantic search rather than exact keyword matching. This makes it essential for handling unstructured data (such as text, images, and audio) and understanding complex queries.
Examples
- 1.Quickly finding the knowledge base documents most relevant to a user's question in AI chatbots
- 2.Recommending visually or functionally similar products based on product images or descriptions in e-commerce stores
- 3.Recommending similar content based on your preferences in music or video streaming services