Amazon Web Services和Microsoft Azure提供的服务的比较分析

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Sara Hameed, Syed Hashim Raza Bukhari, Syeda Umm E Abiha Rizvi, Meerab Tahir, Farhan Aadil
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引用次数: 0

摘要

不同的小型或大型企业得出的结论是,将数据移动到云端更方便。近几十年来,AWS和Azure尽最大努力提供相对经济实惠的即时解决方案。这两种云平台的理解范围都很广,所以用户很难做出正确的选择,因为数据的保密性,更好的存储容量,最重要的是选择一个合理的平台。本文深入分析了Azure和AWS提供的可比较的功能和服务。考虑到安全性、存储、定价和机器学习服务,突出了两个平台的优缺点。它批判性地考察了线性回归模型的实现及其性能。此外,还进行了一项调查,以确保用户知道首选哪个云服务提供商。在机器学习服务的基础上,有更多云经验的人更喜欢Azure machine learning Studio,而不是Amazon SageMaker。Azure的表现优于AWS,达到了70%的准确率,而AWS的准确率只有60%。同样,在安全性、存储和定价方面,Azure因其灵活、易于使用的服务而成为首选。因此,从方法论来看,可以得出Azure优于AWS的结论。然而,只有考虑业务需求才能做出正确的选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Comparative Analysis on the Services Offered by Amazon Web Services and Microsoft Azure

A Comparative Analysis on the Services Offered by Amazon Web Services and Microsoft Azure

Different small or large-scale enterprises came to the conclusion that moving data to the cloud is more convenient. In recent decades, AWS and Azure have tried their best to provide comparatively affordable and instant solutions. Both cloud platforms are extensive to understand, so it is difficult for users to make the right choice because of data confidentiality, better storage capacity, and, most importantly, to select a reasonable platform. This paper is an in-depth analysis of the comparable capabilities and services offered by Azure and AWS. The strengths and weaknesses of both platforms are highlighted considering security, storage, pricing, and machine learning services. It critically examines the implementation of the linear regression model and its performance. Furthermore, a survey was conducted to ensure that the users know which cloud service provider is preferred. On the basis of machine learning services, people with more experience in the cloud preferred Azure Machine Learning Studio over Amazon SageMaker. Azure outperformed AWS, achieving an accuracy of 70%, whereas AWS managed only 60%. Similarly, in cases of security, storage, and pricing, Azure was preferred because of its flexible, easy-to-use services. Therefore, from the methodology, it is concluded that Azure was preferred over AWS. However, the right choice can only be made by considering the business needs.

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来源期刊
Concurrency and Computation-Practice & Experience
Concurrency and Computation-Practice & Experience 工程技术-计算机:理论方法
CiteScore
5.00
自引率
10.00%
发文量
664
审稿时长
9.6 months
期刊介绍: Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.
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