Abstract
The Literature survey exhibits lack of quality research work in field of database(s) when it comes to task of performing comparison between real-world database entities. In this research paper, we have compared and contrast between the two open-source RDBMS (Relational database management system): MySQL and MongoDB. Comparison between two databases was done on basis of database operations, such as insertion, deletion, selection, projection et al. It is true that selection of the database in application depends entirely on database operations and we observed that in some database operations and applications MySQL performed better than MongoDB whereas in some applications MongoDB resulted in better performance. For the evaluation and analysis we obtained the real-time traces of diabetic dataset comprising of 100,000 records with 51 columns and put it to test for efficiency and performance to both the RDBMS and in the end the database operation execution time was recorded and analyzed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Grover, P., Johari, R.: Disaster Big Data AnalysiS WIPS Symposium. In 3rd International Conference on Big Data Analytics (BDA), Delhi University, Springer, Dec 2014
Bhardwaj, V., Johari, R.: Big Data Analysis: Issues and Challenges. In IEEE International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO), VIIT, Visakhapatnam, Andhra Pradesh, Jan 2015
Grover, P., Johari, R.: BCD: Big Data, Cloud Computing and Distributed Computing. In IEEE Global Conference on Communication Technologies (GCCT-2015) Kanyakumari, TamilNadu, April 2015
Bhardwaj, V., Johari, R.; Priti bhardwaj query execution evaluation in wireless network using MyHadoop. In 4th IEEE International Conference on Reliability, Infocom Technologies and Optimization (ICRITO 2015), AMITY University, Sept 2015
Boicea, A., Radulescu, F.: Laura Ioana Agapin: MongoDB vs Oracle—database comparison: In: 2012 Third International Conference on Emerging Intelligent Data and Web Technologies (2012)
Esteves, R.M., Hacker, T., Rong, C.: A new approach for accurate distributed cluster analysis for Big Data: competitive K-Means. Int. J. Big Data Intell. 1(1/2), 50–64 (2014)
Wu, C., Kumar, V., Quinlan, J.R., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G.J., Ng, A., Liu, B., Yu, P.S., Zhou, Z., Steinbach, M., Hand, D.J., Steinberg, D.: In: 1 Top 10 Algorithms in Data Mining. Springer, London (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media Singapore
About this paper
Cite this paper
Purva Grover, Rahul Johari (2016). MVM: MySQL Versus MongoDB. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 436. Springer, Singapore. https://doi.org/10.1007/978-981-10-0448-3_75
Download citation
DOI: https://doi.org/10.1007/978-981-10-0448-3_75
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-0447-6
Online ISBN: 978-981-10-0448-3
eBook Packages: EngineeringEngineering (R0)