An Evaluation of Big Data Architectures

Valerie Garises, José Quenum

Abstract

In this paper, we present a novel evaluation of architectural patterns and software architecture analysis using Architecture-based Tradeoff Analysis Method (ATAM). To facilitate the evaluation, we classify the Big Data intrinsic characteristics into quality attributes. We also categorised existing architectures following architectural patterns. Overall, our evaluation clearly shows that no single architectural pattern is enough to guarantee all the required quality attributes. As such, we recommend a combination of more than one pattern. The net effect of this would be to increase the benefits of each architectural pattern and then support the design of Big Data software architectures with several quality attributes.

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Paper Citation


in Harvard Style

Garises V. and Quenum J. (2019). An Evaluation of Big Data Architectures.In Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-377-3, pages 152-159. DOI: 10.5220/0007840801520159


in Bibtex Style

@conference{data19,
author={Valerie Garises and José Quenum},
title={An Evaluation of Big Data Architectures},
booktitle={Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2019},
pages={152-159},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007840801520159},
isbn={978-989-758-377-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - An Evaluation of Big Data Architectures
SN - 978-989-758-377-3
AU - Garises V.
AU - Quenum J.
PY - 2019
SP - 152
EP - 159
DO - 10.5220/0007840801520159