# What is vector search?

**Assumed Knowledge**: Vectors\
**Target Audience**: General developers\
**Reading Time:** 3 minutes

**What is vector search?**

Vector search is the process of finding the most similar vectors to itself. If you are unfamiliar with vectors, I recommend reading about them [here](https://learn.getvectorai.com/what-are-vectors/untitled).

![Image Vector Search aims to identify the closest vectors based on given images.](https://1051526003-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MTAoGc3QCIn04xUpURg%2F-MTDcLBOotfJ3lrOVFy2%2F-MTIhIrLsO0E7gYiFD60%2Fimage.png?alt=media\&token=1dfc72d8-b168-4874-a259-c2ee44209acc)

Although we initially used the analogy of vectors as fingerprints in our introduction, vectors actually have additional properties that allow them to be useful in practical applications. These include: 

1. Similar data have similar vectors.
2. You can measure the similarity of these vectors statistically in a number of different ways.

The most common algorithms that are used are called **nearest neighbor algorithms**. You can read more about them [here](https://en.wikipedia.org/wiki/Nearest_neighbor_search).

**Why is vector search important?**

If you can find similar vectors based on the data - this means, you can provide different ways of linking data in ways individuals may have never considered. Linguistically - you can now link sentences based on semantics as opposed to relying on co-occurrences of words (used in traditional word search). Similarly, for image search, you can use reverse image search and personalised image search -- allowing for better recommendations for searches. If you are interested in vector search applications, you can read about them [here](https://learn.getvectorai.com/what-are-vectors/untitled/applications-of-vectors).