Comparative Study of Big Query, Redshift, and Snowflake

Keywords

Data warehousing, cloud computing, performance analysis, scalability, cost-efficiency, cloud platforms.

How to Cite

[1]
Venkata Soma, “Comparative Study of Big Query, Redshift, and Snowflake”, N. American. J. of Engg. Research, vol. 3, no. 2, Jun. 2022, Accessed: Nov. 27, 2024. [Online]. Available: http://najer.org/najer/article/view/34

Abstract

In the present era of the intense utilization of big data, effective data warehousing solutions are necessary for the management and analysis of larger volumes of structured and unstructured data. The rapid emergence of cloud computing has transformed the data warehouse inclusion techniques, cost-effectiveness and scalability over the traditional warehousing solutions. This research paper examines the evolution of data warehousing within cloud platforms by emphasizing the cost implications and performance metrics. The well-known cloud-based solutions such as "Amazon Redshift", "Snowflake" and "Google Big Query" are analyzed within this paper focusing on their query performance, architecture and integration abilities. This paper also highlights the potential issues related to cloud computing. The findings of this research underline the transformative influence of cloud data warehousing on the decision-making process of an organization 

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright (c) 2022 North American Journal of Engineering Research

Downloads

Download data is not yet available.