Implementing vector databases in C# with kd-trees - Part 1
Starting today, we embark on a journey to explore the inner workings of vector databases. These databases have surged in popularity in recent years due to the growing demands of artificial intelligence. They allow us to efficiently store and query multidimensional data. In this series of articles, we will examine how vector databases differ from conventional relational databases, why it is important to promote them, and how to implement them in C#.
Vector databases have already been discussed in previous articles on this website, and we encourage readers to refer to those for a foundational understanding. In this series, we will delve deeper into the inner workings by uncovering the underlying data structures such as kd-trees.
- Implementing vector databases in C# with kd-trees - Part 2
- Implementing vector databases in C# with kd-trees - Part 3
- Implementing vector databases in C# with kd-trees - Part 4
- Implementing vector databases in C# with kd-trees - Part 5
- Implementing vector databases in C# with kd-trees - Part 6
The subsequent textbooks prove useful for concluding this series.
Foundations of Multidimensional and Metric Data Structures (Samet)
Introduction to Algorithms (Cormen, Leiserson, Rivest, Stein)
Without further ado and as usual, let's begin with a few prerequisites to correctly understand the underlying concepts. Continue here.