It’s important to have a good understanding of these algorithms and how to apply them effectively in different scenarios.

So, let’s deep dive into each of them and find out what they are, how they work and when to use them.

1. Consistent Hashing

Consistent hashing is a technique used in distributed systems to efficiently distribute data among multiple nodes. It is used to minimize the amount of data that needs to be transferred between nodes when a node is added or removed from the system.

The basic idea behind consistent hashing is to use a hash function to map each piece of data to a node in the system. Each node is assigned a range of hash values, and any data that maps to a hash value within that range is assigned to that node.

When a node is added or removed from the system, only the data that was assigned to that node needs to be transferred to another node. This is achieved by using a concept called virtual nodes. Instead of assigning each physical node a range of hash values, multiple virtual nodes are assigned to each physical node. Each virtual node is assigned a unique range of hash values, and any data that maps to a hash value within that range is assigned to the corresponding physical node.

When a node is added or removed from the system, only the virtual nodes that are affected need to be reassigned, and any data that was assigned to those virtual nodes is transferred to another node. This allows the system to scale dynamically and efficiently, without requiring a full redistribution of data each time a node is added or removed.

Overall, consistent hashing provides a simple and efficient way to distribute data among multiple nodes in a distributed system. It is commonly used in large-scale distributed systems, such as content delivery networks and distributed databases, to provide high availability and scalability.