Open Access   Article Go Back

A Comparitive Study on Mongo and Cassandra Database For Data Clustering

R. Sasikala1

Section:Review Paper, Product Type: Journal Paper
Volume-06 , Issue-11 , Page no. 147-151, Dec-2018

Online published on Dec 31, 2018

Copyright © R. Sasikala . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: R. Sasikala, “A Comparitive Study on Mongo and Cassandra Database For Data Clustering,” International Journal of Computer Sciences and Engineering, Vol.06, Issue.11, pp.147-151, 2018.

MLA Style Citation: R. Sasikala "A Comparitive Study on Mongo and Cassandra Database For Data Clustering." International Journal of Computer Sciences and Engineering 06.11 (2018): 147-151.

APA Style Citation: R. Sasikala, (2018). A Comparitive Study on Mongo and Cassandra Database For Data Clustering. International Journal of Computer Sciences and Engineering, 06(11), 147-151.

BibTex Style Citation:
@article{Sasikala_2018,
author = {R. Sasikala},
title = {A Comparitive Study on Mongo and Cassandra Database For Data Clustering},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2018},
volume = {06},
Issue = {11},
month = {12},
year = {2018},
issn = {2347-2693},
pages = {147-151},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=560},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=560
TI - A Comparitive Study on Mongo and Cassandra Database For Data Clustering
T2 - International Journal of Computer Sciences and Engineering
AU - R. Sasikala
PY - 2018
DA - 2018/12/31
PB - IJCSE, Indore, INDIA
SP - 147-151
IS - 11
VL - 06
SN - 2347-2693
ER -

           

Abstract

Databases provide data storage, extraction and manipulation by using SQL language. It has emerged as a backend to support Big Data applications. It is mainly characterized by horizontal scalability, schema-free data models, and easy cloud deployment. There are various NoSQL databases and the performance varies with different types based on node capacity, number of cores, replication actor, and different workloads. Hence, it is important to compare them in terms of their performance and verify how the performance is related to the different database. This paper focuses on comparison of Cassandra, MongoDB and HBase which are the most commonly used NoSQL databases. This comparison between NoSQL databases deploys them on yahoo cloud platform which uses different types of virtual machines and cluster sizes to study the effect of different configurations. The final result shows the performance of databases at different workload levels and the result can be compared to find out the best among these two databases. In this paper, the comparison of two data bases which are mongo db and Cassandra db algorithm are used to produce the result which is the best db for future data base.

Key-Words / Index Term

BigData, MongoDB, Cassandra db, Virtual machine

References

[1] Venkat N Gudivada,Dhana Rao,Vijay V Raghavan,”Nosql systems for Big Data Management “IEEE 2014,DOI 10.1109/SERVICES .2014.42,pp:190-197.
[2] Thomas Sandholm,Dongman Lee,”Notes on Cloud Computing Principles”in Journal of Cloud Computing:Advances,Systems and applications,springer 2014.
[3] Divyakant Agarwal,Sudipto Das,Amr EI Abbadi, ”Bigdata and Cloud Computing:Current State and Future opportunities”,ACM 2011.
[4] Nani Fadzlina Naim, Ahmad Ihsan MohdYassin, Wan Mohd Ameerul Wan Zamri, Suzi Seroja Sarnin, ”Mysql Database for storage of finger print data” IEEE 2011, DOI 10.1109/UKSIM.2011.62,pp:293-298.
[5] Sudhanshu Kulshreshta, Shelly Sachdeva, ”Performance for Data Storage-DB4o and Mysql Databases”, IEEE 2014.
[6] Mehul Nalin Vora, ”Hadoop-HBase for Large Scale Data” , IEEE 2011,pp:601-605.
[7] Gansen Zhao, Weichai Huang, ShunlinLiang, Yong Tang, ”Modelling MongoDB with Relational Model”, IEEE 2013,DOI 10.1109/EIDWT.2013.25,pp:115-121.
[8] Shalini Ramanathan, Savita Goel, Subramanian Alagumlai, ”Comparison of Cloud Database: Amazon‟s SimpleDB and Google‟s BigTable” ,in IEEE 2011 and International Journal of Computer Science Issues(IJCSI), Vol 8,Issue 6,No 2,Nov 2011,ISSN:1694-0814.
[9] Jing Han, Hai Hong E, Guan Le, Jian Du, ”Survey on Nosql Databases” IEEE 2011, pp:363-366.