Faiss: An Introduction to Vector Databases239

Vector databases are a specialized type of database designed to store and manage vectors, which are arrays of numbers that represent data points. Unlike traditional databases that store structured data in tables, vector databases are optimized for storing and querying high-dimensional data. This makes them ideal for a wide range of applications, including image search, natural language processing, and machine learning.

Faiss is a popular open-source vector database library written in C++. It provides a comprehensive set of tools for storing, indexing, and searching vectors. Faiss is used by a variety of companies and organizations, including Facebook, Google, and Microsoft. In this tutorial, we will provide a gentle introduction to Faiss and show you how to use it to build a simple vector database.

Getting Started

To get started with Faiss, you will need to install the library. You can do this by following the instructions on the Faiss website (/facebookresearch/faiss). Once you have installed Faiss, you can create a new vector database by calling the IndexFactory class. The following code shows how to create a new index with 100 dimensions:```cpp
#include
int main() {
// Create a new index with 100 dimensions
faiss::Index* index = faiss::index_factory(100, "Flat");
// Add some vectors to the index
std::vector vectors = {
{0.1, 0.2, 0.3},
{0.4, 0.5, 0.6},
{0.7, 0.8, 0.9}
};
index->add(3, ());
// Search the index for the nearest neighbors of a query vector
std::vector query = {0.1, 0.2, 0.3};
std::vector neighbors;
std::vector distances;
index->search(1, (), 10, (), ());
// Print the results
for (int i = 0; i < 10; i++) {
std::cout