Skip to main content

Response Times Comparison of MongoDB and PostgreSQL Databases in Specific Test Scenarios

  • 99 Accesses

Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 436)

Abstract

Today, phones, tablets, commercial software, and many different devices are constantly generating data. These produced data should be accessed later on, such as software in business processes or business intelligence. Therefore, these generated data must be stored. There are many popular ways to store data constantly growing in size. All these options come with certain advantages and disadvantages. In this study, a performance comparison will be made between the PostgreSQL database, which is one of the relational databases used for data storage for many years, and the MongoDB database, which is one of the document databases, which has become increasingly popular in recent years, in certain test scenarios. In addition, the properties of relational databases and document databases are given. As a result of the study, similar data and test scenarios created in two databases and different test scenarios in terms of performance were examined, and response times were compared.

Keywords

  • PostgreSQL
  • MongoDB
  • Relational database
  • NoSQL database

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-031-01984-5_15
  • Chapter length: 11 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   64.99
Price excludes VAT (USA)
  • ISBN: 978-3-031-01984-5
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   84.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.

References

  1. Doğan, K., Arslantekin, S.: Büyük Veri: Önemi, Yapısı ve Günümüzdeki Durum. Ankara Univ. J. Faculty Langu. History Geogr. 56(1), 15–36 (2016)

    Google Scholar 

  2. Codd, E.F.: A relational model of data for large shared data banks. Commun. ACM 13(6), 377–387 (1970)

    CrossRef  Google Scholar 

  3. Ward, M.: NoSQL database in the cloud: MongoDB on AWS. Amazon Web Serv. E-J. 1–13 (2013)

    Google Scholar 

  4. Baron, J., Kotecha, S.: Storage options in the AWS cloud traditional vs . cloud - based storage alternatives. Amazon Web Serv. 1–34 (2013)

    Google Scholar 

  5. Vitolo, C., Elkhatib, Y., Reusser, D., Macleod, C.J.A., Buytaert, W.: Web technologies for environmental big data. Environ. Model. Softw. 63, 185–198 (2015)

    CrossRef  Google Scholar 

  6. Kang, Y.S., Park, I.H., Rhee, J., Lee, Y.H.: MongoDB-based repository design for IoT-generated RFID/sensor big data. IEEE Sens. J. 16(2), 485–497 (2016)

    CrossRef  Google Scholar 

  7. Liu, Y., Wang, Y., Jin, Y.: Research on the improvement of MongoDB Auto-Sharding in cloud environment. In: ICCSE 2012 7th International Conference on Computer Science and Education, pp. 851–854. IEEE, Melbourne, Australia (2012)

    Google Scholar 

  8. Politowski, C., Maran, V.: Comparação de Performance entre PostgreSQL e MongoDB. In: Escola Regional de Banco de Dados. Sao Francisco do Soul, Brazil (2014)

    Google Scholar 

  9. Jung, M.G., Youn, S.A., Bae, J., Choi, Y.L.: A study on data input and output performance comparison of MongoDB and PostgreSQL in the big data environment. In: 8th International Conference on Database Theory and Application DTA, pp. 14–17. IEEE, Jeju, Korea (2015)

    Google Scholar 

  10. Tang, E., Fan, Y.: Performance comparison between five NoSQL databases. In: 2016 7th International Conference on Cloud Computing and Big Data, CCBD, pp. 105–109. IEEE, Macau, China (2016)

    Google Scholar 

  11. Agarwal, K., Rajan, K.S.: Analyzing the performance of NoSQL vs. SQL databases for spatial and aggregate queries. In: Free and Open-Source Software for Geospatial (FOSS4G) Conference Proceedings 17 (2017)

    Google Scholar 

  12. Sharma, M., Sharma, V.D., Bundele, M.M.: Performance analysis of RDBMS and No SQL databases: PostgreSQL, MongoDB and Neo4j. In: 3rd International Conference and Workshops on Recent Advances and Innovations in Engineering ICRAIE, pp. 22–25. IEEE, Jaipur, India (2018)

    Google Scholar 

  13. Hajjaji, Y., Farah, I.R.: Performance investigation of selected NoSQL databases for massive remote sensing image data storage. In: 2018 4th International Conference on Advanced Technologies for Signal and Image Processing ATSIP, pp. 1–6. IEEE, Sousse, Tunisia (2018)

    Google Scholar 

  14. Makris, A., Tserpes, K., Spiliopoulos, G., Zissis, D., Anagnostopoulos, D.: MongoDB Vs PostgreSQL: a comparative study on performance aspects. GeoInformatica 25(1), 241–242 (2021)

    CrossRef  Google Scholar 

  15. Virtualbox website. https://www.oracle.com/tr/virtualization/virtualbox/. Accessed 09 Jan 2022

  16. Dordevic, B., Timcenko, V., Pavlovic, O., Davidovic, N.: Performance comparison of native host and hyper-based virtualization VirtualBox. In: 2021 20th International Symposium INFOTEH, pp. 17–19. IEEE, East Sarajevo, Bosnia and Herzegovina (2021)

    Google Scholar 

  17. Vagrantup website. https://www.vagrantup.com/. Accessed 01 Jan 2022

  18. Centos website. https://www.wikizero.com/tr/CentOS. Accessed 12 Jan 2022

  19. Anderson, C.: Docker. IEEE Softw. 32(3), 102–105 (2015)

    CrossRef  Google Scholar 

  20. Merkel, D.: Docker: lightweight Linux containers for consistent development and deployment docker : a little background under the hood. Linux Journal 2014(239), 2–7 (2014)

    Google Scholar 

  21. Dotnet website. https://docs.microsoft.com/tr-tr/dotnet/core/. Accessed 10 Jan 2022

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Emin Güney .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Güney, E., Ceylan, N. (2022). Response Times Comparison of MongoDB and PostgreSQL Databases in Specific Test Scenarios. In: Seyman, M.N. (eds) Electrical and Computer Engineering. ICECENG 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 436. Springer, Cham. https://doi.org/10.1007/978-3-031-01984-5_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-01984-5_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-01983-8

  • Online ISBN: 978-3-031-01984-5

  • eBook Packages: Computer ScienceComputer Science (R0)