Skip to main content
SpringerLink
Log in

A Review on Database and Transaction Models in Different Cloud Application Architectures

  • Conference paper
  • First Online:
Proceedings of Second International Conference on Sustainable Expert Systems

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 351))

Abstract

Cloud computing applications are completely focused on scalable applications and optimized resource utilization. Due to the growing demands in the cloud, the application architecture gets evolved with many features, which are suitable to work with distributed systems. When comparing the monolithic, SOA and microservice architecture, the microservice is found to be the favoring architecture of the cloud. Similar to application architecture, the database model has also taken a shift from RDBMS to NoSQL and NewSQL models. This paper reviews the application architectures analyze their characteristics based on their performance when working with the suitable database models and their associated transactional models. It also examines some of the successful cloud applications, deployed under the distributed systems, with suitable architecture that favors the demands of the cloud.

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
$34.99 /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 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping 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. Pandian AP, Smys S (2020) Effective fragmentation minimization by cloud enabled back up storage. J Ubiquitous Computi Commun Technol (UCCT) 2(01):1–9

    Google Scholar 

  2. Slimani S, Hamrouni T, Ben Charrada F (2021) Service-oriented replication strategies for improving quality-of-service in cloud computing: a survey. Cluster Comput 24:361–392. https://doi.org/10.1007/s10586-020-03108-z

  3. Tomarchio O, Calcaterra D, Modica GD (2020) Cloud resource orchestration in the multi-cloud landscape: a systematic review of existing frameworks. J Cloud Comput 9(1). https://doi.org/10.1186/s13677-020-00194-7

  4. Eldein S, Elhaj AI (2019) A container-based architecture for the design of portable cloud applications. Dissertation of Sudan University of Science & Technology

    Google Scholar 

  5. Hatami-Alamdari E, Etzioni Z (2019) Monolithic architecture vs. multi-layered cloud-based architecture in the CRM application domain

    Google Scholar 

  6. Laigner R et al (2020) From a monolithic big data system to a microservices event-driven architecture. In: 2020 46th Euromicro conference on software engineering and advanced applications (SEAA). IEEE

    Google Scholar 

  7. Faradj R (2018) The run-time impact of business functionality when decomposing and adopting the microservice architecture

    Google Scholar 

  8. Lloyd W, Ramesh S, Chinthalapati S, Ly L, Pallickara S (2018) Serverless computing: an investigation of factors influencing microservice performance. In: 2018 IEEE international conference on cloud engineering (IC2E)

    Google Scholar 

  9. Martinfowler [Online]. https://martinfowler.com/articles/microservices.html

  10. Chris Richardson [online]. https://microservices.io/patterns/monolithic.html

  11. .Chawla H, Kathuria H. Database Design for Microservices. Building Microservices Applications on Microsoft Azure, 225–244. https://doi.org/10.1007/978-1-4842-4828-7_8@@

  12. Richards M (2016) Microservices vs. service-oriented architecture. O’Reilly Media, Inc.

    Google Scholar 

  13. Niknejad N, Ismail W, Ghani I, Nazari B, Bahari M, Hussin ARBC (2020) Understanding service-oriented architecture (SOA): a systematic literature review and directions for further investigation. Inf Syst 101491. https://doi.org/10.1016/j.is.2020.101491

  14. Pulparambil S, Baghdadi Y, Al-Hamdani A, Al-Badawi M (2017) Exploring the main building blocks of SOA method: SOA maturity model perspective. Serv Orient Comput Appl 11:217–232

    Google Scholar 

  15. Cerny, Tom &Donahoo, Michael &Trnka, Michal. “Contextual understanding of microservice architecture: current and future directions” , ACM SIGAPP Applied Computing Review,vol.17,pp. 29–45,Jan (2018)

    Google Scholar 

  16. Ianculescu M, Alexandru A (2020) Microservices—–a catalyzer for better managing healthcare data empowerment. Stud Inf Control 29(2):231–242

    Article  Google Scholar 

  17. Haoxiang W, Smys S (2021) Big data analysis and perturbation using data mining algorithm. J Soft Comput Paradigm (JSCP) 3(01):19–28

    Google Scholar 

  18. Dragoni N, Giallorenzo S, Lafuente AL, Mazzara M, Montesi F, Mustafin R, Safina L (2017) Microservices: yesterday, today and tomorrow. In: Present and ulterior software engineering. Springer, Cham

    Google Scholar 

  19. Wolff E (2016) Microservices: flexible software architecture. Addison-Wesley-Professional

    Google Scholar 

  20. Jamshidi P, Pahl C, Mendonça N, Lewis J, Tilkov S (2018) Microservices: the journey so far and challenges ahead. IEEE Softw 35:24–35

    Google Scholar 

  21. Schneider T (2016) Achieving cloud scalability with microservices and DevOps in the connected car domain. Softw Eng

    Google Scholar 

  22. Kalske M (2018) Transforming monolithic architecture towards microservice architecture. CS thesis, University of Helsinki, Faculty of Science. Department of Computer Science

    Google Scholar 

  23. Yu D et al (2019) A survey on security issues in services communication of microservices‐enabled fog applications. Concurr Comput Pract Exp 31(22):e4436

    Google Scholar 

  24. Antasia D (2019) Best software architecture for MVP, Apr 2019, pp 32–23. Available: https://rubygarage.org/blog/monolith-soa-microservices-serverless

  25. Alam M, Shakil KA (2013) Cloud database management system architecture. UACEE Int J Comput Sci Its Appl 3(1). ISSN 2250-3765

    Google Scholar 

  26. Ali W et al (2019) Comparison between SQL and NoSQL databases and their relationship with big data analytics. Asian J Res Comput Sci 1–10

    Google Scholar 

  27. Moniruzzaman ABM, Hossain S (2013) NoSQL database: new era of databases for big data analytics—classification, characteristics and comparison. Int J Database Theory Appl 6

    Google Scholar 

  28. Makrisa A, Tserpesa K, Andronikoub V, Anagnostopoulosa D (2016) A classification of NoSQL data stores based on key design characteristics. In: Distributed to complete computing, CF2016, pp 18–20, Madrid, Spain, Oct 2016

    Google Scholar 

  29. Lotfy AE, Saleh AI, El-Ghareeb HA, Ali HA (2016) A middle layer solution to support ACID properties for NoSQL databases. J King Saud Univ Comput Inf Sci 28(1):133–145. ISSN 1319-1578. https://doi.org/10.1016/j.jksuci.2015.05.003

  30. Ganesh Chandra D (2015) BASE analysis of NoSQL database. Fut Gener Comput Syst 52(C):13–21

    Google Scholar 

  31. Murazzo M, Gómez P, Rodríguez N, Medel D (2019) Database NewSQL performance evaluation for big data in the public cloud. In: Cloud computing and Big Data, JCC&BD 2019, vol 1050. Springer, Cham

    Google Scholar 

  32. Mapanga I, Kadebu P (2013) Database management systems: a NoSQL analysis. Int J Modern Commun Technol Res (IJMCTR) 1:12–18

    Google Scholar 

  33. Tai S, Eberhardt J, Klems M (2017) Not ACID, not BASE, but SALT: a transaction processing perspective on Blockchains. In: 7th International conference on cloud computing and services science, Apr 2017

    Google Scholar 

  34. Pokorný J (2011) NoSQL databases: a step to database scalability in web environment. Int J Web Inf Syst 9:278–283

    Google Scholar 

  35. Bucchiarone A, Dragoni N, Dustdar S, Larsen ST, Mazzara M (2018) From monolithic to microservices: an experience report from the banking domain. IEEE Softw 35(3):50–55. https://doi.org/10.1109/MS.2018.2141026

    Article  Google Scholar 

  36. Megargel A, Shankararaman V, Walker DK (2020) Migrating from monoliths to cloud-based microservices: a banking industry example. In: Software engineering in the era of cloud computing. Springer, Cham, pp 85–108

    Google Scholar 

  37. Noor A et al (2019) A framework for monitoring microservice-oriented cloud applications in heterogeneous virtualization environments. In: 2019 IEEE 12th international conference on cloud computing (CLOUD). IEEE

    Google Scholar 

  38. Khaleq AA, Ra I (2019) Agnostic approach for microservices autoscaling in cloud applications. In: 2019 international conference on computational science and computational intelligence (CSCI). IEEE

    Google Scholar 

  39. Kouchaksaraei R, Hadi TD, Karl H (2018) Pishahang: joint orchestration of network function chains and distributed cloud applications

    Google Scholar 

  40. Kramer M, Frese S, Kuijper A (2019) Implementing secure applications in smart city clouds using microservices. Fut Gener Comput Syst 99

    Google Scholar 

  41. Knoche H, Hasselbring W (2018) Using microservices for legacy software modernization. IEEE Softw 35(3)

    Google Scholar 

  42. Gan Y et al (2019) An open-source benchmark suite for microservices and their hardware-software implications for cloud and edge systems. In: Proceedings of the twenty-fourth international conference on architectural support for programming languages and operating systems

    Google Scholar 

  43. Kakivaya G et al (2018) Service fabric: a distributed platform for building microservices in the cloud. In: Proceedings of the thirteenth EuroSys conference

    Google Scholar 

  44. Kiss T et al (2019) Micado—microservice-based cloud application-level dynamic orchestrator. Fut Gener Comput Syst 94:937–946

    Google Scholar 

  45. Marie-Magdelaine N, Ahmed T, Astruc-Amato G (2019) Demonstration of an observability framework for cloud native microservices. In: 2019 IFIP/IEEE symposium on integrated network and service management (IM). IEEE

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Research Department of Computer Science, Shrimathi Devkunvar Nanalal Bhatt Vaishnav College for Women, Chennai, India

    N. Priya

  2. Department of Computer Applications, Madras Christian College, Chennai, India

    E. Punithavathy

Authors
  1. N. Priya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. E. Punithavathy
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Engineering, Tribhuvan University, Kirtipur, Nepal

    Subarna Shakya

  2. Department of Electrical and Computer Engineering, Concordia University, Montréal, QC, Canada

    Ke-Lin Du

  3. Go Perception Laboratory, Cornell University, Ithaca, NY, USA

    Wang Haoxiang

Rights and permissions

Reprints and permissions

Copyright information

© 2022 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

Priya, N., Punithavathy, E. (2022). A Review on Database and Transaction Models in Different Cloud Application Architectures. In: Shakya, S., Du, KL., Haoxiang, W. (eds) Proceedings of Second International Conference on Sustainable Expert Systems . Lecture Notes in Networks and Systems, vol 351. Springer, Singapore. https://doi.org/10.1007/978-981-16-7657-4_65

Download citation

Publish with us

Policies and ethics

Search

Navigation