Difference Between Grid and Cloud Computing

The main difference between grid and cloud computing is that the grid computing refers to a collection of computer resources located at different locations to process a single task while the cloud computing refers to manipulating, configuring and accessing hardware and software resources remotely over the internet.

Grid computing connects multiple devices to solve a computation problem. The servers, personal computers, and workstations run independent tasks, and they are loosely linked by a low-speed network or internet. On the other hand, the cloud computing allows accessing applications and utilities via the internet. The users can create, configure and customize applications online. Security issues are a major drawback in both grid and cloud computing.

Key Areas Covered

1. What is Grid Computing
      – Definition, Functionality
2. What is Cloud Computing
     – Definition, Functionality
3. Difference Between Grid and Cloud Computing
     – Comparison of Key Differences

Key Terms

Grid Computing, Cloud Computing, Hybrid Cloud, IaaS, PaaS, Private Cloud, Public Cloud, SaaS

Difference Between Grid and Cloud Computing - Comparison Summary

What is Grid Computing

Grid computing is a collection of computer resources located in different locations to achieve a common goal. It is a type of distributed system with a non-interactive workload. A grid consists of hardware and software infrastructure.

Main Difference - Grid vs Cloud Computing

Figure 1: Cable Racks at Grid Computing Center

Grid computing connects resource such as PCs, workstations, storage, and servers and provides a mechanism to access them. All grid clients are connected together via a network. These clients are installed with special software called middleware. The network connects to the grid server, and it has its own storage. The users can access the required data through the grid server which handles all administrative tasks.

What is Cloud Computing

Cloud computing refers to manipulating, configuring and accessing hardware and software resources remotely. Cloud computing contains virtual data centers that can provide hardware, software, and resources when required. Therefore, the organizations can access the cloud to obtain the resources. It provides scalability according to the business requirements.

Difference Between Grid and Cloud Computing

Figure 2: Cloud Computing

There are two types of models in cloud computing. They are the deployment models and services models. There are four types of deployment models. They define the access type to the cloud.

Public Cloud – Provide services to the general public. It is not very secure.

Private Cloud – Provide services to a particular organization.

Community Cloud – Provides services to a group of organizations.

Hybrid Cloud – A combination of public and private clouds. The private cloud performs the critical tasks, and the public cloud performs the non-critical tasks.

Furthermore, there are three types of service models in cloud computing as follows.

IaaS (Infrastructure-as-a-Service) – Provides resources such as virtual machines, virtual storage, etc.

PaaS (Platform-as-a-Service) – Provides the runtime environment for applications, development and deployment tools.

SaaS (Software-as-a-Service) – Provides access to the software applications as a service to the end users.

Difference Between Grid and Cloud Computing

Definition

Grid computing is the use of widely distributed computer resources to reach a common goal. Cloud computing is the technology that enables access to shared pools of configurable system resources and higher-level services over the internet. This is the basic difference between grid and cloud computing. 

Computer Resources

Management of computer resources is another difference between grid and cloud computing. The computing resources in grid computing are distributed among different devices located in different locations (Different sites, countries or continents). However, in cloud computing, computing resources are managed centrally in data centers belonging to the cloud service providers.

Main Functionality

In grid computing, the task is divided into several independent subtasks, and each machine on the grid is assigned with a subtask. After completing them, the results are sent back to the main machine. On the other hand, Cloud computing provides resources according to the requirements.

Accessing Method

In grid computing, the users can access the data in the grid computing devices via cooperate networks such as internet or a low-speed network.  In cloud computing, the users can access the resources through the internet.

Management

While the management in grid computing is decentralized, the management in cloud computing is centralized. This is an important difference between grid and cloud computing.

Architecture Type

Grid computing uses distributed architecture whereas cloud computing uses client-server architecture.

Conclusion

The difference between grid and cloud computing is that grid computing refers to a collection of computer resources located at different locations to process a single task while cloud computing refers to manipulating, configuring and accessing hardware and software resources remotely over the internet. In brief, cloud computing is more flexible than grid computing.

Reference:

1. “What Is Grid Computing? – Definition from WhatIs.com.” SearchDataCenter En Español, Available here.
2. Grid Computing | by Bhanu Priya, Education 4u, 14 Aug. 2018, Available here.
3. “Cloud Computing Overview.” Www.tutorialspoint.com, Tutorials Point, Available here.

Image Courtesy:

1. “Cable racks at grid computing center, Fermilab with blue lights” By ENERGY.GOV – (Public Domain) via Commons Wikimedia
2. “Cloud computing” By Sam Johnston using OmniGroup’s OmniGraffle and Inkscape (includes Computer.svg by Sasa Stefanovic)(CC BY-SA 3.0) via Commons Wikimedia

About the Author: Lithmee

Lithmee holds a Bachelor of Science degree in Computer Systems Engineering and is reading for her Master’s degree in Computer Science. She is passionate about sharing her knowldge in the areas of programming, data science, and computer systems.

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