Cloud-Based Grid Computing is the utilization of computers that are connected to a public cloud system to accomplish huge, collaborative projects. It may also use a hybrid of public cloud and some internally owned computer systems. Some examples of these large projects are complex simulations, derivative risk analysis, candidate drug screening, etc.
Commonly, cloud and grid are considered as separate and even competing ideas. Grid computing uses distributed pieces of hardware to meet goals that require a tremendous amount of processing and computing, like real-time accumulation of complex, disparate data. Often, there are debates on the advantages and disadvantages of grid vs. cloud. Many consider grid computing to be superior on the ground of it offering better performance.
However, cloud computing can anticipate demand spikes, and thus offer better scalability. Many believe that cloud computing has now overshadowed grid computing since in place of creating hardware systems, clients can easily seek customized systems from cloud services providers. Cloud computing is mainly utilized by the average organization, whereas grid computing is more often used by large institutions or government agencies. On a technical plane, cloud based grid computing may have a number of hardware elements that are collaborating on large tasks or projects on a public cloud platform.