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Informative Article | Science and Technology | India | Volume 9 Issue 7, July 2020 | Popularity: 4.8 / 10

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Cloud Storage Strategies for High - Performance Analytics: An In - Depth Look at Databases, Data Warehouses, and Object Storage Solutions

Prakash Somasundaram

Abstract: This study delves into the evolving landscape of cloud storage strategies, crucial for high - performance analytics in data - centric enterprises. It focuses on three primary cloud storage solutions: database storage, data warehousing, and object storage, each catering to distinct aspects of data analytics. The research navigates through the nuances of cloud - based services for database management, highlighting the transition from traditional models to dynamic, scalable, and cost - effective cloud databases, including SQL, NoSQL, and NewSQL. Additionally, it examines advanced cloud data warehousing technologies like Amazon Redshift, Google BigQuery, and Snowflake, known for their extensive storage and computational prowess. The paper also explores object storage solutions such as Amazon S3 and Google Cloud Storage, which are ideal for managing large volumes of unstructured data in data lakes. A key element of this research is a comparative analysis of leading cloud service providers ? Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) elucidating their unique strengths in database storage, data warehousing, and object storage solutions. This comprehensive study aims to guide organizations and researchers in selecting appropriate cloud storage strategies, taking into account various data attributes, analytical requirements, compliance mandates, and cost considerations, thereby facilitating informed decision - making in the domain of high - performance analytics.

Keywords: Cloud Storage, Database Storage, Data Warehousing, Object Storage, Cloud Computing, Analytics

Edition: Volume 9 Issue 7, July 2020

Pages: 2004 - 2009

DOI: https://www.doi.org/10.21275/SR24203232850

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