Evaluating Scalable Solutions: A Comparative Study of AWS, Azure, and GCP

Evaluating Scalable Solutions: A Comparative Study of AWS, Azure, and GCP

Registration ID: IJNRD_226645

Published ID: IJNRD2109004

DOI: Click Here to Get

Er. SUMIT SHEKHAR , DR. PRIYA PANDEY , ER. OM GOEL

AWS, Azure, GCP, cloud computing, scalability, cost-effectiveness, performance, security, customer support, hybrid cloud, machine learning, data analytics.

Cloud computing has become a cornerstone for modern businesses, enabling scalable and flexible infrastructure solutions that support a wide range of applications and services. Among the most prominent cloud service providers are Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), each offering a unique set of features, pricing models, and performance metrics. This comparative study aims to evaluate these three major cloud platforms to provide insights into their strengths and weaknesses, focusing on scalability, cost-effectiveness, performance, security, and customer support. AWS, as a pioneer in cloud services, has established a vast ecosystem with a comprehensive suite of services, ranging from computing and storage to machine learning and IoT. Its pay-as-you-go pricing model and a wide array of instances make it an attractive option for enterprises of all sizes. However, its complexity and multitude of services can be overwhelming for new users, potentially leading to higher costs if not managed properly. Microsoft Azure, deeply integrated with other Microsoft products, provides seamless interoperability for businesses heavily reliant on Windows and Microsoft software. Its hybrid cloud capabilities and enterprise-focused solutions make it a preferred choice for organizations seeking to integrate on-premises infrastructure with cloud resources. Azure's pricing is competitive, but it often requires a thorough understanding of its licensing models to optimize costs. Google Cloud Platform stands out with its cutting-edge technology in data analytics and machine learning, leveraging Google's expertise in AI and data processing. GCP offers flexible pricing plans and strong support for containerized applications, appealing to tech-savvy businesses and startups focusing on innovation and development. Despite its technological prowess, GCP has a smaller market share compared to AWS and Azure, which might impact the availability of resources and third-party integrations. The study analyzes various use cases and benchmarks to compare the performance and scalability of AWS, Azure, and GCP. It highlights key factors that influence decision-making, such as total cost of ownership (TCO), ease of use, and customer satisfaction. Additionally, the research examines security frameworks and compliance standards, evaluating how each platform addresses the growing concerns of data privacy and protection. Through this comparative analysis, businesses can gain a deeper understanding of the strategic advantages and limitations of each cloud provider. The study aims to assist decision-makers in selecting the most suitable cloud platform based on their specific needs, operational requirements, and budget constraints. By examining real-world case studies and industry expert opinions, this research provides a comprehensive overview of the current cloud computing landscape and its future direction.

Published Paper   E-Certificate

"Evaluating Scalable Solutions: A Comparative Study of AWS, Azure, and GCP", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 8, page no.20-33, August-2024, Available :https://ijnrd.org/papers/IJNRD2109004.pdf

Volume 9 Issue 8, August-2024

Pages : 20-33

Paper Reg. ID: IJNRD_226645

Published Paper Id: IJNRD2109004

Downloads: 000121257

Research Area: Engineering

Country: -, -, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2109004.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2109004

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

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