SpringerLink
Log in

Building a NoSQL ERP

  • Conference paper
  • First Online:
Proceedings of Seventh International Congress on Information and Communication Technology

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 448))

Abstract

Enterprise resource planning (ERP) systems are needed in many business activities. Small and medium enterprises (SMEs) are not well-served by current ERPs, as such systems are hard to tailor. This prompts us to experiment with building an ERP on top of a NoSQL database, which intends to be more flexible, as it is based on JSON and not on a relational data model. We present a novel ERP solution specifically designed to grow and evolve as the world changes. The ERP is for a service company which bills for time spent on customer projects. The work involves various challenges: data modelling, query specification, write and read performance analysis, versioning, user interface generation and query optimisation. Here, we report on the performance of a NoSQL ERP using MongoDB and show that writes are fast and queries and reports are fast enough.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Aboutorabi SH, Rezapour M, Moradi M, Ghadiri N (2015) Performance evaluation of SQL and MongoDB databases for big e-commerce data. In: 2015 international symposium on computer science and software engineering (CSSE), pp 1–7

    Google Scholar 

  2. Andreoli R, Cucinotta T, Pedreschi D (2021) RT-MongoDB: a NoSQL database with differentiated performance. In: Proceedings of 11th international conference on cloud computing and services science, CLOSER’21, SCITEPRESS, pp 77–86

    Google Scholar 

  3. Barth C, Koch S (2019) Critical success factors in ERP upgrade projects. Ind Manag Data Syst 119(3):656–675

    Article  Google Scholar 

  4. Cayres LU, de Lima BS, Garcia RE, Correia RCM (2020) Analysis of Node.js application performance using MongoDB drivers. In: Information technology and systems: proceedings of ICITS, vol 1137 of advances in intelligent systems and computing. Springer, Berlin, pp 213–222

    Google Scholar 

  5. Daly D (2021) Creating a virtuous cycle in performance testing at MongoDB. In: ICPE’21: ACM/SPEC international conference on performance engineering (ICPE). ACM, pp 33–41

    Google Scholar 

  6. Daly D (2021) Performance engineering and database development at MongoDB. In: ICPE’21: ACM/SPEC international conference on performance engineering (ICPE). ACM, p 129

    Google Scholar 

  7. Davoudian A, Chen L, Liu M (2018) A survey on NoSQL stores. ACM Comput Surv 51:2 Apr

    Google Scholar 

  8. De Michelis G, Dubois E, Jarke M, Matthes F, Mylopoulos J, Schmidt JW, Woo C, Yu E (1998) A three-faceted view of information systems. Commun ACM 41(12):64–70 Dec

    Article  Google Scholar 

  9. Faith T, Nguyen D, Torii D, Schenck P, Hestermann C (2020) Magic quadrant for cloud ERP for product-centric enterprises. https://www.gartner.com/doc/reprints?id=1-1ZB9RIQ1 &ct=200624 &st=sb

  10. Gibson N, Holland CP, Light B (1999) Enterprise resource planning: a business approach to systems development. In: 32nd annual Hawaii international conference on system sciences HICSS-32. IEEE Computer Society

    Google Scholar 

  11. Guerrero S (2021) Consuming data in Fiori Applications. In: Custom Fiori Applications in SAP HANA. Springer, Berlin, pp 37–80

    Google Scholar 

  12. Huang C, Cahill MJ, Fekete AD, Röhm U (2020) Deciding when to trade data freshness for performance in MongoDB-as-a-service. In: 36th international conference on data engineering, ICDE’20. IEEE, pp 1934–1937

    Google Scholar 

  13. Huang Q, Rahim MM, Foster S, Anwar M (2021) Critical success factors affecting implementation of cloud ERP systems: a systematic literature review with future research possibilities. In: 54th Hawaii international conference on system sciences, HICSS 2021. ScholarSpace, pp 1–10

    Google Scholar 

  14. Idreos S, Callaghan M (2020) Key-value storage engines. In: Proceedings of 2020 ACM SIGMOD international conference on management of data, SIGMOD ’20, ACM, pp 2667–2672

    Google Scholar 

  15. Ingo H, Daly D (2020) Automated system performance testing at MongoDB. In: Proceedings of 8th international workshop on testing database Systems, DBTest@SIGMOD 2020. ACM, pp 3:1–3:6

    Google Scholar 

  16. Kamsky A (2019) Adapting TPC-C benchmark to measure performance of multi-document transactions in MongoDB. Proc VLDB 12(12):2254–2262

    Article  Google Scholar 

  17. Kim RY (2020) The impact of COVID-19 on consumers: Preparing for digital sales. IEEE Eng Manag Rev 48(3):212–218

    Article  Google Scholar 

  18. Liu ZH, Hammerschmidt B, McMahon D, Chang H, Lu Y, Spiegel J, Sosa AC, Suresh S, Arora G, Arora V (2020) Native JSON datatype support: maturing SQL and NoSQL convergence in Oracle database. Proc VLDB 13(12):3059–3071

    Article  Google Scholar 

  19. Llano-Ríos TF, Khalefa M, Badia A (2020) Experimental comparison of relational and NoSQL document systems: the case of decision support. In: Performance Evaluation and Benchmarking—12th TPC technology conference, TPCTC’20, vol 12752 of LNCS. Springer, Berlin, pp 58–74

    Google Scholar 

  20. Lu F, Fang T, Zhang Z, Li S, Chen J, An H, Han W (2019) Improving the performance of MongoDB with RDMA. In: 17th IEEE international conference on smart City; 5th IEEE international conference on data science and systems, HPCC/SmartCity/DSS19. IEEE, pp 1004–1010

    Google Scholar 

  21. Makris A, Tserpes K, Spiliopoulos G, Anagnostopoulos D (2019) Performance evaluation of MongoDB and PostgreSQL for spatio-temporal data. In: Proceedings of workshops of EDBT/ICDT’19, vol 322 of CEUR Workshop Proceeings

    Google Scholar 

  22. Marimuthu T, van der Merwe A, Gerber A (2021) Systematic literature review of essential enterprise architecture management dimensions. In Proceedings of 6th international congress on information and communication technology—ICICT’21, vol 1, vol 235 of LNCS. Springer, Berlin, pp 381–391

    Google Scholar 

  23. Meier A, Kaufmann M (2019) SQL and NoSQL databases. Springer, Berlin

    Google Scholar 

  24. MongoDB I (2021) MongoDB. https://www.mongodb.com

  25. Nielsen J (1993) Usability engineering. Morgan Kaufmann, Amsterdam

    Book  Google Scholar 

  26. NPMFaker (2021) Faker.js—generate massive amounts of fake data in the browser and node.js. https://www.npmjs.com/package/faker

  27. Parker Z, Poe S, Vrbsky SV (2013) Comparing NoSQL MongoDB to an SQL DB. In: ACM Southeast regional conference 2013, SE’13. ACM, pp 5:1–5:6

    Google Scholar 

  28. Ravat, F, Song J, Teste O, Trojahn C (2020) Efficient querying of multidimensional RDF data with aggregates: comparing NoSQL, RDF and relational data stores. Int J Inf Manag 54:102089

    Google Scholar 

  29. Senaya SK, van der Poll JA, Schoeman M (2022) Towards a framework to address enterprise resource planning (ERP) challenges. In: Proceedings of 6th international congress on information and communication technology. Springer, Berlin, pp 57–71

    Google Scholar 

  30. Soransso RASN, Cavalcanti MC (2018) Data modeling for analytical queries on document-oriented DBMS. In: Proceedings of 33rd annual ACM symposium on applied Computing, SAC’18, pp 541–548

    Google Scholar 

  31. van Beijsterveld JA, Van Groenendaal WJ (2016) Solving misfits in ERP implementations by SMEs. Inf Syst J 26(4):369–393

    Article  Google Scholar 

  32. Wang J, Trummer I, Basu D (2021) UDO: universal database optimization using reinforcement learning. Proc VLDB 14(13):3402–3414

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. FHNW University of Applied Arts and Sciences Northwestern Switzerland, School of Business, Institute for Information Systems, Olten, Switzerland

    Ela Pustulka, Stefan von Arx & Lucia de Espona

Authors
  1. Ela Pustulka
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Stefan von Arx
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lucia de Espona
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ela Pustulka .

Editor information

Editors and Affiliations

  1. Middlesex University, London, UK

    **n-She Yang

  2. The University of Reading, Reading, UK

    Simon Sherratt

  3. JIS University, Kolkata, India

    Nilanjan Dey

  4. Global Knowledge Research Foundation, Ahmedabad, India

    Amit Joshi

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Pustulka, E., von Arx, S., de Espona, L. (2023). Building a NoSQL ERP. In: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds) Proceedings of Seventh International Congress on Information and Communication Technology. Lecture Notes in Networks and Systems, vol 448. Springer, Singapore. https://doi.org/10.1007/978-981-19-1610-6_59

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-1610-6_59

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1609-0

  • Online ISBN: 978-981-19-1610-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation