---
title: Types of Search
---

## Full Text Search

Full text search is a technique that finds entries in a collection of text based on the presence of specific keywords and phrases.
For instance, consider a movie review site that lets users search for movies. Movie titles would benefit from full text search, since users are
likely looking for exact keywords like `Harry` and `Potter`.

## Similarity Search

Similarity search matches documents based on semantic meaning. In the movie review example, movie descriptions may benefit from similarity search.
Users that query for `the boy who lived` may be looking for `Harry Potter` even though these phrases share no common keywords.

This is achieved through a technique called vector search. A vector is a fixed array of numeric values that captures
the semantic meaning of a piece of text. Vectors are typically generated by embedding models.

## Hybrid Search

Many modern applications use a combination of full text and similarity search. This process is called [hybrid search](/documentation/guides/hybrid).
Typical hybrid search techniques involve calculating separate full text and similarity scores for the result set and combining the scores into a hybrid score.