Research Article | OPEN ACCESS
From Relational Databases to NoSQL Databases: Performance Evaluation
Ahmad Abdullah and Qingfeng Zhuge
College of Computer Science, Chongqing University, Chongqing 400044, China
Research Journal of Applied Sciences, Engineering and Technology 2015 4:434-439
Received: April 23, 2015 | Accepted: May 22, 2015 | Published: October 05, 2015
Abstract
In nowadays applications, the amount of data in the database grows exponentially. So, the DBMS must process these huge amounts of data as fast as possible. The main aim of this study is to prove that NoSQL databases process big data faster than relational database. The changing in applications, user and infrastructure characteristics, mostly of the Web 2.0 domain and cloud platform, led to explosion of data sources and massive workloads. These huge amounts of data have raised the problems of storage and usability of data as the usual Relational Database Management Systems (RDBMS) were unable to handle the exponentially growing data on a single in house server (vertical scalability). Furthermore, the required time to process these big data is an issue. The study implements prototype which verifies performance argument. The performance evaluation compares the insertion and retrieval speeds between MongoDB as NoSQL database and MySQL as relational database. The benchmarking performed shows that MongoDB is faster than MySQL in the most of scenarios we chose, particularly when we deal with huge amount of data.
Keywords:
MongoDB, MySQL, NoSQL databases, performance evaluation, relational databases, speed comparison,
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Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
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