DocumentCode :
3717175
Title :
BigFUN: A performance study of big data management system functionality
Author :
Pouria Pirzadeh;Michael J. Carey;Till Westmann
Author_Institution :
University of California Irvine, Irvine, USA
fYear :
2015
Firstpage :
507
Lastpage :
514
Abstract :
In this paper, we report on an evaluation of four representative Big Data management systems (BDMSs): Mon-goDB, Hive, AsterixDB, and a commercial parallel shared-nothing relational database system. In terms of features, all offer to store and manage large volumes of data, and all provide some degree of query processing capabilities on top of such data. Our evaluation is based on a micro-benchmark that utilizes a synthetic application that has a social network flavor. We analyze the performance results and discuss the lessons learned from this effort. We hope that this study will inspire future domain-centric evaluations of BDMSs with a focus on their features.
Keywords :
"Big data","Benchmark testing","Chirp","Data models","Databases","Social network services","Electronic mail"
Publisher :
ieee
Conference_Titel :
Big Data (Big Data), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/BigData.2015.7363793
Filename :
7363793
Link To Document :
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