In the field of artificial intelligence large specific database by industry amounts of data require efficient management and processing. As we move into more advanced applications of AI, such as image recognition, voice search, or recommendation engines, the nature of data becomes more intricate. This is where vector databases come into play. Unlike traditional databases store scalar values, vector databases are specifically design to handle multidimensional. Data points, often referred to as vectors. Representing data in numerous dimensions, these vectors can be thought of as arrows pointing in one direction. Having a certain magnitude in space.
What is a vector database?
A vector database is a specific type of database that what are the stages of the sales process? stores information in the form of multidimensional vectors that represent certain characteristics or qualities.
The number of dimensions in each vector can vary widely, from a few to several thousand, depending on the complexity and detail of the data. This data can include text, images, audio, and video, is transformed into vectors using a variety of processes. machine learning models, word embedding.
The main advantage of a vector database is its ability to quickly and accurately locate This allows for searches based on semantic or contextual relevance, rather than based solely on exact matches or set criteria, the case with conventional databases.
How does a vector database work?
Traditional databases store simple data, uab directory such as words and numbers, in table format. Vector databases, however, work with complex data called vectors and use unique search methods.
While regular databases look for exact matches of data, vector databases look for the closest match using specific similarity measurements.
Vector databases use special search techniques known as approximate nearest . which includes methods such as hashing and graph-based searches.
To really understand how vector databases work . they differ from traditional relational databases like SQL , we first need to understand the concept of embedding.
Unstructured data, such as text, images, and audio, lack a predefined format. Poses challenges for traditional databases.