Performance Evaluation of IoT Data Management Using MongoDB Versus MySQL Databases in Different Cloud Environments

Mahmoud Moustafa Eyada,Mohammed M El Genidy,Walaa Saber,Fathy Amer

doi:10.1109/access.2020.3002164

Mahmoud Moustafa Eyada, Mohammed M El Genidy + Show 2 more

Open Access

https://doi.org/10.1109/access.2020.3002164

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Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 39	License type: CC BY 4.0

Affiliation: Port Said University, Cairo University

Abstract

The Internet of Things (IoT) introduces a new challenge for Database Management Systems (DBMS). In IoT, large numbers of sensors are used in daily lives. These sensors generate a huge amount of heterogeneous data that needs to be handled by the appropriate DBMS. The IoT has a challenge for the DBMS in evaluating how to store and manipulate a huge amount of heterogeneous data. DBMS can be categorized into two main types: The Relational DBMSs and the Non-relational DBMSs. This paper aims to provide a thorough comparative evaluation of two popular open-source DBMSs: MySQL as a Relational DBMS and MongoDB as a Non-relational DBMS. This comparison is based on evaluating the performance of inserting and retrieving a huge amount of IoT data and evaluating the performance of the two types of databases to work on resources with different specifications in cloud computing. This paper also proposes two prediction models and differentiates between them to estimate the response time in terms of the size of the database and the specifications of the cloud instance. These models help to select the appropriate DBMS to manage and store a certain size of data on an instance with particular specifications based on the estimated response time. The results indicate that MongoDB outperforms MySQL in terms of latency and the database size through increasing the amount of tested data. Moreover, MongoDB can save resources better than MySQL that needs resources with high capabilities to work with less performance.

Highlights

Nowadays Internet of Things (IoT) technology become the backbone of many industries like smart home systems, industrial control systems, monitoring of pharmacies and hospitals, open-source web data and weather stations
The results show that through increasing the number of connected sensors per station and increasing workloads, the difference in latency between MongoDB and MySQL is increased in favor of MongoDB
WORK In this paper, a comparison between MongoDB and MySQL has been implemented to evaluate the performance of both databases to deal with a large scale of heterogeneous IoT data

Summary

INTRODUCTION

Nowadays Internet of Things (IoT) technology become the backbone of many industries like smart home systems, industrial control systems, monitoring of pharmacies and hospitals, open-source web data and weather stations. Using IoT technology generates a large amount of heterogeneous data like texts, numbers, audio, videos, and pictures These types of data need to be transferred, processed and stored in a cloud server. M. Eyada et al.: Performance Evaluation of IoT Data Management using MongoDB versus MySQL Databases are supposed to be distributed with high scalability and availability. The main objective of this paper is to find an effective way to manage and store a large amount of heterogeneous data in appropriate DBMS. This objective is implemented by performing comprehensive experiments to compare and evaluate the performance of the two types of databases: MySQL as a Relational DBMS and MongoDB as a Non-relational DBMS.

BACKGROUND

DATASETS AND METHODS

Findings

CONCLUSION AND FUTURE WORK