A Comparative Study of AWS, Azure, and GCP for Scalable Big Data Solutions in Wholesale Product Distribution

Abstract

Due to the increasing volume of information generated worldwide, every day more companies are in search of new ways to process and gain business value from data. Part of this circumstance can be attributed to the constant growth of the Internet, which is a factor of considerable relevance for the creation of New Information and a binding constraint for the collection of a Big Set of Data. In this way, organizations that have data in enormous volume and variety have, at their disposal nowadays, new forms of treatment of this information that guarantee efficiency in the decision-making process. In this niche, Cloud Computing is inserted, breaking paradigms on the way that companies treat their data. Thus, with the democratization of Data Processing, an increasing number of companies are looking for Cloud Providers capable of putting Data Processing as a Service. In this context, the goal of this research is to perform a comparative study of the main providers of Cloud Computing services, analyzing the main features of their respective products, pros and cons, architectural frameworks, tools, set of features, and pricing. In addition, special attention was given to the services offered for the creation of Data Lakes, as well as the possibilities offered by the companies studied for the processing of Big Data in a way that allows obtaining business value in business solutions. The present study is exploratory and descriptive, employing a qualitative and quantitative approach. Finally, this research presented a consideration of a possible architecture for the available tools and models. The results pointed to a favorable scenography for the use of technologies by companies, given the new features available for their tools, as well as the lower cost and greater scalability, given the recent price reductions in the services offered. Finally, as an informal contribution to the community, we presented a set of points to be considered for the decision on a Database solution for Big Data.