A Comparative Analysis of Big Data Frameworks: An Adoption Perspective

The emergence of social media, the worldwide web, electronic transactions, and next-generation sequencing not only opens new horizons of opportunities but also leads to the accumulation of a massive amount of data. The rapid growth of digital data generated from diverse sources makes it inapt to use...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Madiha Khalid, Muhammad Murtaza Yousaf
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	big data frameworks fault tolerance stream processing systems distributed frameworks Spark Hadoop Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/8247a092f8b5428583cb0d396aef2478
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:8247a092f8b5428583cb0d396aef2478
record_format	dspace
spelling	oai:doaj.org-article:8247a092f8b5428583cb0d396aef24782021-11-25T16:43:09ZA Comparative Analysis of Big Data Frameworks: An Adoption Perspective10.3390/app1122110332076-3417https://doaj.org/article/8247a092f8b5428583cb0d396aef24782021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/11033https://doaj.org/toc/2076-3417The emergence of social media, the worldwide web, electronic transactions, and next-generation sequencing not only opens new horizons of opportunities but also leads to the accumulation of a massive amount of data. The rapid growth of digital data generated from diverse sources makes it inapt to use traditional storage, processing, and analysis methods. These limitations have led to the development of new technologies to process and store very large datasets. As a result, several execution frameworks emerged for big data processing. Hadoop MapReduce, the pioneering framework, set the ground for forthcoming frameworks that improve the processing and development of large-scale data in many ways. This research focuses on comparing the most prominent and widely used frameworks in the open-source landscape. We identify key requirements of a big framework and review each of these frameworks in the perspective of those requirements. To enhance the clarity of comparison and analysis, we group the logically related features, forming a feature vector. We design seven feature vectors and present a comparative analysis of frameworks with respect to those feature vectors. We identify use cases and highlight the strengths and weaknesses of each framework. Moreover, we present a detailed discussion that can serve as a decision-making guide to select the appropriate framework for an application.Madiha KhalidMuhammad Murtaza YousafMDPI AGarticlebig data frameworksfault tolerancestream processing systemsdistributed frameworksSparkHadoopTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 11033, p 11033 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	big data frameworks fault tolerance stream processing systems distributed frameworks Spark Hadoop Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	big data frameworks fault tolerance stream processing systems distributed frameworks Spark Hadoop Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Madiha Khalid Muhammad Murtaza Yousaf A Comparative Analysis of Big Data Frameworks: An Adoption Perspective
description	The emergence of social media, the worldwide web, electronic transactions, and next-generation sequencing not only opens new horizons of opportunities but also leads to the accumulation of a massive amount of data. The rapid growth of digital data generated from diverse sources makes it inapt to use traditional storage, processing, and analysis methods. These limitations have led to the development of new technologies to process and store very large datasets. As a result, several execution frameworks emerged for big data processing. Hadoop MapReduce, the pioneering framework, set the ground for forthcoming frameworks that improve the processing and development of large-scale data in many ways. This research focuses on comparing the most prominent and widely used frameworks in the open-source landscape. We identify key requirements of a big framework and review each of these frameworks in the perspective of those requirements. To enhance the clarity of comparison and analysis, we group the logically related features, forming a feature vector. We design seven feature vectors and present a comparative analysis of frameworks with respect to those feature vectors. We identify use cases and highlight the strengths and weaknesses of each framework. Moreover, we present a detailed discussion that can serve as a decision-making guide to select the appropriate framework for an application.
format	article
author	Madiha Khalid Muhammad Murtaza Yousaf
author_facet	Madiha Khalid Muhammad Murtaza Yousaf
author_sort	Madiha Khalid
title	A Comparative Analysis of Big Data Frameworks: An Adoption Perspective
title_short	A Comparative Analysis of Big Data Frameworks: An Adoption Perspective
title_full	A Comparative Analysis of Big Data Frameworks: An Adoption Perspective
title_fullStr	A Comparative Analysis of Big Data Frameworks: An Adoption Perspective
title_full_unstemmed	A Comparative Analysis of Big Data Frameworks: An Adoption Perspective
title_sort	comparative analysis of big data frameworks: an adoption perspective
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/8247a092f8b5428583cb0d396aef2478
work_keys_str_mv	AT madihakhalid acomparativeanalysisofbigdataframeworksanadoptionperspective AT muhammadmurtazayousaf acomparativeanalysisofbigdataframeworksanadoptionperspective AT madihakhalid comparativeanalysisofbigdataframeworksanadoptionperspective AT muhammadmurtazayousaf comparativeanalysisofbigdataframeworksanadoptionperspective
_version_	1718413029004017664

A Comparative Analysis of Big Data Frameworks: An Adoption Perspective

Ejemplares similares