Types of Distributed Systems - Cloud Computing

Four Types of Distributed Systems

Under the umbrella of distributed systems, there are a few different architectures. Broadly, we can divide distributed cloud systems into four models:

Client-Server Model

In this model, the client fetches data from the server directly then formats the data and renders it for the end-user. To modify this data, end-users can directly submit their edits back to the server.

For example, companies like Amazon that store customer information. When a customer  updates their address or phone number, the client sends this to the server, where the server updates the information in the database.

Three-Tier Model

The three-tier model introduces an additional tier between client and server — the agent tier.

This middle tier holds the client data, releasing the client from the burden of managing its own information.  The client can access its data through a web application, typically. Through this, the client application’s and the user’s work is reduced and automated easily.

For example, a cloud storage space with the ability to store your files and a document editor. Such a storage solution can make your file available anywhere for you through the internet, saving you from managing data on your local machine.

Multi-Tier Model

Enterprises need business logic to interact with various backend data tiers and frontend presentation tiers. This logic sends requests to multiple enterprise network services easily. That’s why large organizations prefer the n-tier or multi-tier distributed computing model.

For example, an enterprise network with n-tiers that collaborate when a user publishes a social media post to multiple platforms. The post itself goes from data tier to presentation tier.

Peer-to-Peer Model

Unlike the hierarchical client and server model, this model comprises peers. Each peer can act as a client or server, depending upon the request it is processing. These peers share their computing power, decision-making power, and capabilities to work better in collaboration.

For example, blockchain nodes that collaboratively work to make decisions regarding adding, deleting, and updating data in the network.