Data Mining and Knowledge Engineering

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Data Performance Evaluation Using RDBMS and non-RDBMS


Affiliations
1 Department of CSE, AMC Engineering College, Bengaluru., India
2 Department of CSE, AMC Engineering College, Bengaluru., India
3 Department of CSE, AMC Engineering College, Bengaluru, India
     

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The Internet of Things (IoT) initiates a challenge for the Database Management System (DBMS) in estimating how to store and handle very excess amount of heterogeneous data. DBMS is classified as two types: Relational DBMS and Non-Relational DBMS. This paper seeks to provide an estimation of two open-source DBMSs: MySQL as one of the Relational DBMS and MongoDB as one of the Non-Relational DBMS. The contrast is depended on estimating the performance of inserting and restoring the excess amount of data and assessing the performance of both types of databases with different stipulations in the cloud computing. This paper introduces two different models which are used for prediction and finds the difference between them to assess the latency in which that data responds efficiently and the database size. Thus the models of prediction help to choose the suitable database to store and maintain the data. The result shows that the MongoDB is more and more efficient than that of the MySQL database. In which MongoDB is able to save or store resources and data better and efficient than that of the MySQL.

Keywords

IoT, DBMS, SQL, MySQL, NoSQL, MongoDB, AWS, Cloud, Multiple Non-Linear Regressions
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  • Data Performance Evaluation Using RDBMS and non-RDBMS

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Authors

D Salangai Nayagi
Department of CSE, AMC Engineering College, Bengaluru., India
J Anju
Department of CSE, AMC Engineering College, Bengaluru., India
A Ashwini
Department of CSE, AMC Engineering College, Bengaluru., India
Divya Krishnan
Department of CSE, AMC Engineering College, Bengaluru, India
K Tejaswini
Department of CSE, AMC Engineering College, Bengaluru., India

Abstract


The Internet of Things (IoT) initiates a challenge for the Database Management System (DBMS) in estimating how to store and handle very excess amount of heterogeneous data. DBMS is classified as two types: Relational DBMS and Non-Relational DBMS. This paper seeks to provide an estimation of two open-source DBMSs: MySQL as one of the Relational DBMS and MongoDB as one of the Non-Relational DBMS. The contrast is depended on estimating the performance of inserting and restoring the excess amount of data and assessing the performance of both types of databases with different stipulations in the cloud computing. This paper introduces two different models which are used for prediction and finds the difference between them to assess the latency in which that data responds efficiently and the database size. Thus the models of prediction help to choose the suitable database to store and maintain the data. The result shows that the MongoDB is more and more efficient than that of the MySQL database. In which MongoDB is able to save or store resources and data better and efficient than that of the MySQL.

Keywords


IoT, DBMS, SQL, MySQL, NoSQL, MongoDB, AWS, Cloud, Multiple Non-Linear Regressions

References