How Vector Databases Work

By ADMIN Team

Learn what makes vector databases popular for AI and ML applications.

Vector databases are emerging as critical tools for AI, “offering unparalleled efficiency and accuracy in handling the vast, intricate datasets generated by generative AI models,” says Pavan Belagatti.

“A vector database is a kind of database that is designed to store, index and retrieve data points with multiple dimensions, which are commonly referred to as vectors,” Belagatti explains. And, in this article, he explores how vector databases work and provides a hands-on tutorial.

Related content

How vector databases work and when they're used
Vector databases are one of the critical components for AI-based applications such as ChatGPT that rely on vector search queries to extract knowledge context from vast amounts of data.

more »
Vector databases for data-driven artificial intelligence
Artificial intelligence requires special databases that rely on similarity searches for more effective processing of diverse data and embeddings to improve scalability, flexibility, and interpretability.

more »
When you should and should not use NoSQL databases
Tables are an established format for storing information in databases, but they don't always fit the bill – which is just one argument of many that speaks for NoSQL.

more »
Workflow-based data analysis with KNIME
They say data is "the new oil," but all that data you collect is only valuable if it leads to new insights. An open source analysis tool called KNIME lets you analyze data through graphical workflows – without the need for programming or complex spreadsheet manipulation.

more »
Prepare, analyze, and visualize data with R
The free R programming language and software environment for statistical computing and graphics is well supported, has great flexibility, and is easily automated.

more »