CAP Theorem in Distributed Systems

 

A decentralized system is a way of dividing the system into different nodes. Several nodes connect the systems to share and communicate the data across the network. Distributed system is widely used for Cloud computing, web-servicing, big data processing, etc. Google Cloud, AWS, Azure, etc use this method to store data at a larger place from a big network of systems, also these platforms provide services to their customers regarding online storage, data classification across multiple servers, deploying the websites, a much more efficient framework of decentralized system and much more. However, data is also dispersed from the centre and located at multiple places to provide the customer with a good environment and quicker response to the request. Therefore, it is an efficient way of organizing data. Still, paradoxically there are some complications and challenges faced by these systems while implications and also deal with the failure in the network. One of the fundamental trade-offs of these systems is the CAP theorem. CAP theorem is an abbreviation of Consistency, Availability, and Partitioning.

1. Consistency:

It means that each node of the system provides the same information whenever it is accessed. Any read access that happens from any location provides with the latest written value.

 

2. Availability:

Every system across the network is readily available and accessible whenever there is any read request in the network, it doesn't matter if any node in the network is operational or not. Data from the nodes is always provided to the customer.

3. Partition Tolerance:

This means that the system continues to function despite any number of communication failures and delays of responses between the nodes. This means the system can tolerate the failure of links and nodes in the network.

Combinational Structure with CAP

Moving further to What the CAP theorem actually is? It states that in any partitioning system, the system must choose between any of the three functionalities and the trade-off the third one. That's why it is very important while designing the distributed system, which of the two functionalities must be chosen for a good network architecture. In other words, a system can be either CA (consistent and available), CP (consistent and partition tolerant), or AP (available and partition tolerant). Thereby, in the partitioning system, there is always a trade-off of the third feature in CAP.

CAP theorem (also called Brewer’s theorem) states that a distributed database system can only guarantee two out of these three characteristics: Consistency, Availability, and Partition Tolerance. (Educative.io - Website)

References:

1. CAP theorem - Wikipedia
2. CAP Theorem in DBMS