Skip to main content
Springer Nature Link
Log in

Comparative Analysis of Structured and Un-Structured Databases

  • Conference paper
  • First Online:
Computational Intelligence, Communications, and Business Analytics (CICBA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 776))

  • 1519 Accesses

Abstract

The introduction of relational database systems helped in faster transactions compared to the existing system for handling structured data. However, in course of time the cost of storing huge volume of unstructured data became an issue in traditional relational database systems. This is where some unstructured database systems like NoSQL databases were introduced in the domain to store unstructured data. This paper focuses on four different structured(PostgreSQL) and un-structured database systems(MongoDB, OrientDB and Neo4j). In this paper, we will eventually see the different kind of data models they follow and analyze their comparative performances by experimental evidences.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Similar content being viewed by others

References

  1. OrientDB Manual - version 2.1.x. http://orientdb.com/docs/2.1/. Accessed 7 Jan 2017

  2. PostgreSQL: Downloads (1996). https://www.postgresql.org/download/. Accessed 5 Jan 5 2017

  3. MongoDB. (2 January 2017). MongoDB Download center. https://www.mongodb.com/download-center#community. 9 Jan 2017

  4. Robomongo (2017). https://robomongo.org/download. Acessed 9 January 2017

  5. LTD, O. (17 January 2017). Download OrientDB v2.2.17 community and enterprise edition. http://orientdb.com/download/. Accessed 9 Jan 2017

  6. Technology, N.: Download neo4j community edition - neo4j graph database (2017). https://neo4j.com/download/community-edition/. Accessed 6 Jan 2017

  7. Postgresql: Documentation: 7.1: Architecture (1996). https://www.postgresql.org/docs/7.1/static/arch.html. Accessed 9 Jan 2017

  8. Banker, K.: MongoDB in action (2011)

    Google Scholar 

  9. Carlson, J.L.: Redis in Action (2013)

    Google Scholar 

  10. Crockford, D.: The application/JSON media type for javascript object notation (JSON) (2006)

    Google Scholar 

  11. Hadjigeorgiou, C.: RDBMS vs NoSQL: Performance and scaling comparison (2013)

    Google Scholar 

  12. Han, J., Haihong, E., Le, G., Du, J.: Survey on nosql database. In: 2011 6th International Conference on Pervasive Computing and Applications (ICPCA), pp. 363–366 (2011)

    Google Scholar 

  13. Hawkins, T., Plugge, E., Membrey, P.: The definitive guide to MongoDB: the noSQL database for cloud and desktop computing (2011)

    Google Scholar 

  14. Jatana, N., Puri, S., Ahuja, M., Kathuria, I., Gosain, D.: A survey and comparison of relational and non-relational database. Int. J. Eng. Res. Technol. 1(6) (2012)

    Google Scholar 

  15. Kaur, K., Rani, R.: Modeling and querying data in nosql databases. In: 2013 IEEE International Conference on Big Data, pp. 1–7 (2013)

    Google Scholar 

  16. Leavitt, N.: Will nosql databases live up to their promise? Computer 43(2), 12–14 (2010)

    Article  Google Scholar 

  17. Lennon, J.: Introduction to JSON. In: Beginning CouchDB, pp. 87–105 (2009)

    Google Scholar 

  18. Miller, J.J.: Graph database applications and concepts with Neo4j. In: Proceedings of the Southern Association for Information Systems Conference, vol. 2324, Atlanta, GA, USA (2013)

    Google Scholar 

  19. Momjian, B.: Postgresql performance tuning. Linux J. 2001(88), 3–9 (2001)

    Google Scholar 

  20. Moniruzzaman, A.B.M., Hossain, S.A.: Nosql database: new era of databases for big data analytics-classification, characteristics and comparison. arXiv preprint (2013). arXiv:1307.0191

  21. Nayak, A., Poriya, A., Poojary, D.: Type of NOSQL databases and its comparison with relational databases. Int. J. Appl. Inf. Syst. 5(4), 16–19 (2013)

    Google Scholar 

  22. Panzarino, O.: Learning Cypher (2014)

    Google Scholar 

  23. Rumbaugh, J., Blaha, M., Premerlani, W., Eddy, F., Lorensen, W.E.: Object-oriented modeling and design, vol. 199 (1991)

    Google Scholar 

  24. Tesoriero, C.: Getting Started with OrientDB (2013)

    Google Scholar 

  25. Tsichritzis, D., Lochovsky, F.H.: Hierarchical data-base management: a survey. ACM Comput. Surv. (CSUR) 8(1), 105–123 (1976)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Technology, Jadavpur University, Kolkata, India

    Madhupa Sanyal, Samiran Chattopadhyay & Kartick Chandra Mondal

  2. School of Mobile Computing, Jadavpur University, Kolkata, India

    Anindita Sarkar Mondal

Authors
  1. Anindita Sarkar Mondal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Madhupa Sanyal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Samiran Chattopadhyay
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kartick Chandra Mondal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kartick Chandra Mondal .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    J. K. Mandal

  2. Department of Computer and System Sciences, Visva Bharati University, Bolpur Santiniketan, West Bengal, India

    Paramartha Dutta

  3. Department of Information Technology, Calcutta Business School, Kolkata, India

    Somnath Mukhopadhyay

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Nature Singapore Pte Ltd.

About this paper

Cite this paper

Mondal, A.S., Sanyal, M., Chattopadhyay, S., Mondal, K.C. (2017). Comparative Analysis of Structured and Un-Structured Databases. In: Mandal, J., Dutta, P., Mukhopadhyay, S. (eds) Computational Intelligence, Communications, and Business Analytics. CICBA 2017. Communications in Computer and Information Science, vol 776. Springer, Singapore. https://doi.org/10.1007/978-981-10-6430-2_18

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-6430-2_18

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6429-6

  • Online ISBN: 978-981-10-6430-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics