Capturing Anomalies of Cassandra Performance with Increase in Data Volume: A NoSQL Analytical Approach

  • Ramesh DharavathEmail author
  • Anand Kumar
  • Vinod Kumar Dharavath
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 37)


NoSQL database technology has been doing rounds since the early 1990s, but it was the exponential growth of internet and the rise of web applications that lead to a dynamic surge in the popularity of NoSQL databases. The BigTable research by Google (2006) and the Dynamo research by Amazon (2007) paved the way for databases which could develop with agility and operate at any scale. Cassandra and MongoDB have emerged as the two most widely used NoSQL database and hence either of the two is preferred depending on the data problem user is attempting to solve. This paper describes the underlying principles as well as the differences between both the databases. We focus on showing the anomaly in performance of Cassandra as the data volume increases and at the same time we compare its performance with that of MongoDB. We establish how important factor is data volume in choosing either of the databases for an application. Extensive experiments have been carried out to scale the performance in terms of anomaly similarities, and the future scope is pinpointed.


NoSQL database Sharding Consistency Indexing Replication 



This work is partially supported by the Indian Institute of Technology (ISM), Dhanbad that comes under the administrative and financial control of the Ministry of Human Resource Development (MHRD), Government of India. The authors express their gratitude towards the Department of Computer Science and Engineering at IIT (ISM) for providing all the necessary support to carry out the research work.


  1. 1.
    L. Okman, N. Gal-Oz, Y. Gonen, E. Gudes, J. Abramov, Security issues in nosql databases, in 2011 IEEE 10th international conference on Trust, security and privacy in computing and communications (TrustCom) (IEEE, 2011, November), pp. 541–547Google Scholar
  2. 2.
    O.P. Richard, A Scalable relational database model for cloud computing (Doctoral dissertation) (Makerere University, 2005)Google Scholar
  3. 3.
    E. Dede, M. Govindaraju, D. Gunter, R.S. Canon, L. Ramakrishnan, Performance evaluation of a mongodb and hadoop platform for scientific data analysis, in Proceedings of the 4th ACM workshop on scientific cloud computing (ACM, 2013, June), pp. 13–20Google Scholar
  4. 4.
    A. Marcus, The nosql ecosystem. Arch. Open Source Appl., 185–205 (2011)Google Scholar
  5. 5.
    D. Ramesh, A.K. Jain, C. Kumar, C, Implementation of atomicity and snapshot isolation for multi-row transactions on column oriented distributed databases using rdbms, in 2012 International conference on communications, devices and intelligent systems (CODIS) (IEEE, 2012, December), pp. 298–301Google Scholar
  6. 6.
    Y. Li, S. Manoharan, A performance comparison of SQL and NoSQL databases, in Communications, computers and signal processing (PACRIM), 2013 IEEE pacific rim conference on (IEEE, 2013, August), pp. 15–19Google Scholar
  7. 7.
    V. Abramova, J. Bernardino, NoSQL databases: MongoDB vs Cassandra, in Proceedings of the international C* conference on computer science and software engineering (ACM, 2013, July), pp. 14–22Google Scholar
  8. 8.
    J. Han, E. Haihong, G. Le, J. Du, Survey on NoSQL database, in 2011 6th international conference on Pervasive computing and applications (ICPCA) (IEEE, 2011, October), pp. 363–366Google Scholar
  9. 9.
    A. Chebotko, A. Kashlev, S. Lu, A big data modeling methodology for apache cassandra, in 2015 IEEE international congress on big data (bigdata congress) (IEEE, 2015, June), pp. 238–245Google Scholar
  10. 10.
    S. Dhingra, S. Sharma, P. Kaur, C. Dabas, Fault tolerant streaming of live news using multi-node Cassandra, in 2017 Tenth international conference on contemporary computing (IC3) (IEEE, 2017, August), pp. 1–5Google Scholar
  11. 11.
  12. 12.
    D. Ramesh, A. Sinha, S. Singh, Data modelling for discrete time series data using cassandra and mongodb, in 2016 3rd international conference on recent advances in information technology (RAIT) (2016, March, IEEE), pp. 598–601Google Scholar
  13. 13.
    D. Featherston, Cassandra: principles and application, in Department of computer science university of illinois at Urbana-champaign (2010)Google Scholar
  14. 14.
    Z. Parker, S. Poe, S.V. Vrbsky, Comparing nosql mongodb to an sql db. In Proceedings of the 51st ACM southeast conference (ACM, 2013, April), p. 5Google Scholar
  15. 15.
    P. Membrey, E. Plugge, D. Hawkins, The definitive guide to MongoDB: the noSQL database for cloud and desktop computing (Apress, 2011), pp. 55–56Google Scholar
  16. 16.
    K. Banker, MongoDB in action (Manning Publications Co, 2011)Google Scholar
  17. 17.
    Introduction to BSON:
  18. 18.
  19. 19.
    K. Chodorow, MongoDB: The definitive guide: powerful and scalable data storage (O’Reilly Media, Inc, 2013), pp. 231–239Google Scholar
  20. 20.
    Y. Liu, Y. Wang, Y. Jin, Research on the improvement of MongoDB Auto-Sharding in cloud environment. In 2012 7th international conference on Computer science & education (ICCSE) (IEEE, 2012, July), pp. 851–854Google Scholar
  21. 21.
    D. Ramesh, E. Khosla, S.N. Bhukya, Inclusion of e-commerce workflow with NoSQL DBMS: MongoDB document store, in 2016 IEEE international conference on computational intelligence and computing research (ICCIC) (IEEE, 2016, December), pp. 1–5Google Scholar
  22. 22.
    Properties on Cassandra database:
  23. 23.
    MongoDB official documentation.
  24. 24.
    A. Lakshman, P. Malik, Cassandra: a decentralized structured storage system. ACM SIGOPS Oper Syst Rev 44(2), 35–40 (2010)CrossRefGoogle Scholar
  25. 25.
  26. 26.
    B.G. Tudorica, C. Bucur, A comparison between several NoSQL databases with comments and notes, in 2011 10th Roedunet International Conference (RoEduNet) (IEEE, 2011, June), pp. 1–5Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringIndian Institute of Technology (Indian School of Mines)DhanbadIndia

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