What's a vector database?

A vector database is a place where developers store specially formatted data to use for machine learning and AI.

TL;DR

A vector database is a place where developers store specially formatted data to use for machine learning and AI.

  • To make large language models more accurate, you need to power them with your own unique data
  • But models have a very specific data diet: they only consume vectors, which are a bunch of numbers
  • Embedding is the process of turning your data (images, text, videos) into vector representations (numbers)
  • Vector databases are specialized places to store these embeddings, and search through + retrieve them when you need them

Vector databases themselves are actually pretty simple, but the context for why they exist is not. So let’s start with that.

Why do we need a vector database in the first place?

Using your data to improve AI models

The point of a vector database is to make it easier for you to integrate your company’s data into a large language model. But why would you want to do that in the first place? The general answer: to make models more accurate and customized to your specific needs.

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