Cloud-Native Data Engineering: Leveraging Azure and GCP for Scalable Data Pipelines

Authors

  • Sandeep Batchu Western Kentucky University, Kentucky, USA Author
  • Raghuvaran Kendyala University of Illinois at Springfield, Illinois, USA Author
  • Nivathan Athiganoor Somasundharam Texas A&M University - Kingsville, TX - USA Author
  • Vivek Sheetal Dhaduvai University of the Cumberlands, Kentucky - USA Author

Keywords:

cloud platforms, data engineering, Azure Data Factory

Abstract

The goal of this research paper is to explore the transforming role of cloud platforms in modern age data engineering workflows which mainly focus on Microsoft Azure and Google Cloud Platform (GCP). Through the help of this study, we explore the capabilities of Azure Data Factory, Azure Synapse Analytics, and GCP's Big Query in the creation of scalable, resilient, and high-performance data pipelines. These services are very crucial for the organizations that are trying to manage large volumes of data efficiency and maintaining flexibility and operational continuity at the same time.

Downloads

Download data is not yet available.

Downloads

Published

22-04-2022

How to Cite

[1]
S. Batchu, R. Kendyala, N. A. Somasundharam, and V. S. Dhaduvai, “Cloud-Native Data Engineering: Leveraging Azure and GCP for Scalable Data Pipelines ”, J. Sci. Tech., vol. 3, no. 2, pp. 182–226, Apr. 2022, Accessed: Mar. 07, 2026. [Online]. Available: https://thesciencebrigade.org/jst/article/view/588

Most read articles by the same author(s)