What is the alternative of consistent hashing?

An alternative to consistent hashing is rendezvous hashing. Consistent hashing has been a popular distributed hashing technique used in computer science and distributed systems to achieve load balancing and minimize the need for rehashing when the number of nodes in a system changes.

• However, as systems evolve and new challenges arise, developers are constantly seeking more efficient and effective solutions.
• In this article, we explore alternatives to consistent hashing and delve into techniques that offer improvements in various aspects such as load balancing, distribution uniformity, and ease of implementation.

The Alternative of Consistent Hashing

An alternative to consistent hashing is rendezvous hashing, also known as the highest random weight (HRW) hashing.

• Rendezvous hashing is a technique used for selecting a node in a distributed system to store a piece of data.
• It improves upon consistent hashing by providing better load balancing and reduced data movement when nodes are added or removed from the system.
• In rendezvous hashing, each node and data item is assigned a unique identifier (e.g., a hash value).
• When a data item needs to be stored or retrieved, the system computes a hash value for the item and compares it with the hash values of all nodes. The node with the highest hash value is selected to store or retrieve the data item.

Example:

Suppose we have three nodes in a distributed system, each with a unique hash value (e.g., Node A = 10, Node B = 15, Node C = 20). If a data item is hashed to a value of 12, Node B (with a hash value of 15) would be selected to handle the data item, as it has the highest hash value among the three nodes.

Consistent Hashing Vs. Rendezvous Hashing

Below are the differences between Consistent Hashing and Rendezvous Hashing:

Aspect	Consistent Hashing	Rendezvous Hashing
Load Balancing	May lead to uneven distribution of keys	Tends to distribute keys more evenly among nodes
Data Movement	Requires significant data movement when nodes change	Minimizes data movement when nodes are added or removed
Node Selection	Nodes are selected using a hash function	Nodes are selected based on the highest hash value
Virtual Nodes	Uses virtual nodes to improve load balancing	Does not require virtual nodes for load balancing
Complexity	Relatively simple to implement	Slightly more complex than consistent hashing
Implementation	Maintains a sorted list or ring of hash values	Requires computing hash values for all nodes for each key
Performance	Generally performs well, but load balancing may suffer	Improved load balancing and reduced data movement