Article Review Procedure
Academic Areas and Subjects
Applied Aspects of Information Technology
Search by article
Vol. 4 № 1
Vol. 4 № 2
Vol. 3 № 1
Vol. 3 № 2
Vol. 3 № 3
Vol. 3 № 4
Vol. 2 № 1
Vol. 2 № 2
Vol. 2 № 3
Vol. 2 № 4
Vol. 1 № 1
5 Oct 2021
On October 5, 2021, a business meeting was held between representatives of the EPAM Systems IT Company Denis Grinev and Sergey Garashchuk with the Rector of the State University “Odessa Polytechnic” Gennadii Alexandrovich Oborskiy
17 Sept 2021
International Summer School
15 July 2021
Until November 1, 2021, enrollment in the double degree program of Slovakia 2ouble Degree is carried out.
INFORMATION TECHNOLOGY OF SUPPORTING ARCHITECTURAL SOLUTIONS USING POLYGLOT PERSISTENCE CONCEPT IN LEARNING MANAGEMENT SYSTEMS
This paper shows that performance of the learning management systems heavily depends on the choice, made during designing, of architectural solution for storage and processing of data. Based on analysis of evolution of the various architectural solutions during the information system design, beginning with monolith platform and ending with decentralized microservices, it has been determined that architecture based on microservices for a server side with code-level isolation and database-level decentralization for components is proved to be effective solution for high-performance system complexes for learning management system. However, for implementation of polyglot persistence concept based on multiple database management systems with various logical schemas, there is also a need for developing an information technology to support such architectural solutions. It has been shown that the development of databases for such learning management system, that operate with a large amount of various information, consists of the stages of conceptual, logical and physical modeling, and, precisely during the creation of logical models the requirements for the storage and processing of data, that are used by the selected entities for the implementation of business functions, are determined. The peculiar properties of using relational and non-relational database management systems such as: document, key-value, graph and column storages have been examined and analyzed in detail. A method for automated selection of logical data models based on initial information about a limited context has been developed, then used to develop a classifier. The efficiency of the classifier was tested on a dataset for two hundred thirty entities. As a result of the experiment, the reliability of the classification was ninety-three percent. The advantages of the developed information technology are shown on the example of designing JustStart learning management system. Analysis of the stress testing results of the developed system shows that due to the distribution of the load between the three databases, its average response time with simultaneous operation of one hundred fifty users was one point two seconds. At the same time, simulation of the same number of users with only one database management system, the response time increased and the average was approximately two point six seconds. Thus, the use of the developed information technology of supporting architectural solutions for organizing storage of large volumes of diverse data according to the polyglot persistence concept, that allowed to design and implement learning management system, the performance of which, if it is used simultaneously by a large audience, is on average twice as fast as the average educational resource on the market.
( email@example.com )
Maria G. Glava
, Senior Lecturer
( firstname.lastname@example.org )
( email@example.com )
Olena O. Arsirii
, Dr. of Tech. Sciences, Professor
( firstname.lastname@example.org )
learning management systems; polyglot persistence; microservice architecture; decision trees
1. “List of Top LMS Software Companies of 2020”. Finances Online [Digital Resource]. – Available at: https://financesonline.com/top-20-lmssoftware-companies/. – Active link – 9 May 2020.
2. “Martin Fowler, Microservices” [Digital resource]. – Available at: https://martinfowler.com/ articles/microservices.html. – Active link – 9 May 2020.
3. Martin Fowler, Polyglot Persistence [Digital Resource]. – Available at: https://martinfowler.com/ bliki/PolyglotPersistence.html. – Active link – 10 May 2020.
4. Srivastava, K. & Shekokar, N. (2016). “A Polyglot Persistence approach for E-Commerce business model”, International Conference on Information Science (ICIS), pp. 7-10. DOI: 10.1109/infosci.2016.7845291.
5. “Po stopam luchshih: mikroservisnaja arhitektura v razreze” [Following the steps of the best: microservice architecture breakdown] [Digital Resource]. – Available at: https://proglib.io/p/postopam-luchshih-mikroservisnaya-arhitektura-vrazreze-2019-11-07. – Active link – 9 May 2020 (in Russian).
6. Di Francesco, P., Lago, P. & Malavolta, I. (2018). “Migrating Towards Microservice Architectures: An Industrial Survey”, IEEE International Conference on Software Architecture (ICSA). DOI: 10.1109/icsa.2018.00012.
7. Martinez-Mosquera, D., Navarrete, R. & Lujan-Mora, S. (2020). “Modeling and Management Big Data in Databases”, A Systematic Literature Review. Sustainability, 12(2), 634 p. DOI: 10.3390/su12020634.
8. Storey, V. C. & Song, I.-Y. (2017). “Big data technologies and Management: What conceptual modeling can do”, In: Data & Knowledge Engineering 108, pp. 50-67. DOI: 10.1016/j.datak.2017.01.001.
9. Mohammad Sadoghi, Souvik Bhattacherjee, Bishwaranjan Bhattacharjee & Mustafa Canim. (March 26-29 2018). “L-Store: A Real-time OLTP and OLAP System”, In: Proceedings of the 21st International Conference on Extending Database Technology (EDBT), pp. 540-551. DOI: 10.5441/002/edbt.2018.65.
10. Khine, P. P. & Wang, Z. (2019). “A Review of Polyglot Persistence in the Big Data World”, Information 2019, 10(4), 141 p. DOI: 10.3390/info10040141.
11. Pritchett, D. (2008). “BASE: An ACID alternative”, Queue, 6(3), pp. 48-55. DOI: 10.1145/1394127.1394128.
12. Yashraj Sharma & Yashasvi Sharma. (2019). “Case study of traditional RDBMS and NoSQL database system”. In: International Journal of Research – Granthaalayah, 7(7), pp. 351-359. DOI: 10.5281/zenodo.3364448.
13. Kleppmann, M. (2015). “A Critique of the CAP Theorem”. DOI: 10.17863/CAM.13083.
14. Klemenkov, P. & Kuznetsov, S (2012). “Bol'shie dannye: sovremennye podhody k hraneniju i obrabotke” [Big data: modern approaches to storage and analysis], Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2012; 23. DOI: 10.15514/ISPRAS-2012- 23-9 (in Russian).
15. Pete Aven & Diane Burley. (2017). “Building on Multi-Model Databases”, Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, CA 95472. – Available at: http://info.marklogic.com/rs/371-XVQ-609/images/building-on-multi-model-databases.pdf. – Active link – 10 May 2020.
16. Jiaheng Lu, Irena Holubová & Bogdan Cautis. (2018). “Multi-model Databases and Tightly Integrated Polystores: Current Practices, Comparisons, and Open Challenges”, In: CIKM ’18, October 22- 26, 2018, Torino, Italy. DOI: 10.1145/3269206.3274269.
17. Lu, J. & Holubová, I. (June 2019). “Multimodel Databases”, In: ACM Comput. Surv. 52, 3, Article 55, pp. 1-38. DOI: 10.1145/3323214.
18. Irena Holubova, Meike Klettke & Uta Storl. (2019). “Evolution Management of Multi-model Data”, Springer Nature Switzerland AG 2019. V. Gadepally et al. (Eds.): DMAH 2019/Poly 2019, LNCS 11721, pp. 139-153, 2019. DOI: 10.1007/978-3-030-33752-0_10.
19. Olena O. Arsiri, Alina O. Glumenko & Diana E. Stelmakh. (2018). “Characteristics of the development of an IT-project for creation of open educational resource”, The Third International Research Conference “Project, Program, Portfolio Management, 2018”, Odessa, Ukraine, pp. 21-23.
20. Olena O. Arsiri, Alina O. Glumenko & Diana E. Stelmakh. (May 23-24 2019). “Rozrobka Onlajnovogo Osvіtn''ogo Resursu z Vikoristannjam Bagatovarіantnoї Persistentnostі” [The development of an educational resource based on polyglot persistence], Materials of the Ninth International Scientific Conference of Students and Young Scientists on the 55th Anniversary of the Institute of Computer Systems, “Modern Information Technology – 2019”, MES of Ukraine; Odessa. Nat. polytechnic. univ.; Inst. of computers. Systems, Odessa, Ukraine, Ecology, pp. 97-98 (In Ukrainian).
21. Olena O. Arsiri, Alina O. Glumenko. (23.09.- 25.09.2019), “Rozrobka Onlajnovogo Navchal''nogo resursu z Vikoristannjam Bagatovarіantnoї Persistentnostі” [The development of an educational resource based on polyglot persistence persistence], VII International scientific & technical conference “Informatics. Culture. Technologies”, Odessa, Ukraine, pp. 35-36 (in Ukrainian).
22. Bellatreche, L., Valduriez, P. & Morzy, T. (2018). “Advances in Databases and Information Systems”, In: Inf. Syst Front 20, 1-6 (2018). DOI: 10.1007/s10796-017-9819-2.
23. Jannatul Maowa, A. H. M. Sajedul Hoque, Rashed Mustafa & Mohammad Osiur Rahman. (May 2017). “A Comparative Study on Big Data Handling Using Relational and Non-Relational Data Model”, In: International Journal of Data Mining & Knowledge Management Process (IJDKP), Vol. 7, No. 3. DOI: 10.5121/ijdkp.2017.7302.
24. Klemenkov, P. A. (September 2013). “Postroenie Novostnogo Rekomendatel''nogo Servisa Real''nogo Vremeni s Ispol''zovaniem NoSQL SUBD” [Building real-time news recommendation service using NoSQL DBMS], In: Informatics and Applications, Vol. 7, Issue 3, pp 14-21. DOI: 10.14357/19922264130302 (in Russian).
25. Moniruzzaman, A. B. & Hossain, S.A. (2013). “NoSQL Database: New Era of Databases for Big Data Analytics – Classification, Characteristics and Comparison”, In: International Journal of Database Theory and Application, Vol. 6, No. 4. ArXiv, abs/1307.0191.
26. Li, Z. (2018). “NoSQL Databases”. In: The Geographic Information Science & Technology Body of Knowledge (2nd Quarter 2018 Edition), John P. Wilson (Ed). DOI: 10.22224/gistbok/2018.2.10.
27. Hieu Nguyen (Jack). “The pros and cons of different data formats: key-values vs tuples” [Digital Resource]. – Available at: https://www.freecodecamp.org/news/the-pros-andcons-of-different-data-formats-key-values-vs-tuplesf526ad3fa964/. – Active link – 11 May 2020.
28. Alves Florencio, D., Ricardo Freitas de Oliveira, D., Laisa Soares Xavier Freitas, E. & da Fonseca de Souza, F. (Nov. 2017). “Which Fits Better? A Comparative Analysis about NoSQL KeyValue Databases”, In: IEEE Latin America Transactions, Vol. 15, No. 11, pp. 2251-2256. DOI: 10.1109/TLA.2017.8070434 (in Portuguese).
29. Chevalier, M., El Malki, M., Kopliku, A., Teste, O. & Tournier, R. (2016). “Documentoriented Models for Data Warehouses – NoSQL Document-oriented for Data Warehouses”, In: Proceedings of the 18th International Conference on Enterprise Information Systems, Vol. 1: ICEIS, ISBN 978-989-758-187-8, pp. 142-149. DOI: 10.5220/0005830801420149.
30. Davoudian, A., Chen, L. & Liu, M. (April 2018). “A Survey on NoSQL Stores”, In: ACM Computing Surveys, Vol. 51, No. 2, Article 40. Publication date: 2018, pp. 1-43. DOI: 10.1145/3158661.
31. Ameya Nayak, Anil Poriya & Dikshay Poojary (March 2013). “Type of NOSQL Databases and its Comparison with Relational Databases”, In: International Journal of Applied Information Systems (IJAIS) – ISSN: 2249-0868 Foundation of Computer Science FCS, New York, USA Vol. 5, No. 4.
32. Kumar, K. B. S. & Srividya Mohanavalli, S. (2017). “A performance comparison of documentoriented NoSQL databases”, In: 2017 International Conference on Computer, Communication and Signal Processing (ICCCSP). DOI:10.1109/icccsp.2017.7944071.
33. Weidong Wen, Yang Li, Wenhai Li, Lingfeng Deng & Yanxiang He. (June 2019). “CORES: Towards Scan-Optimized Columnar Storage for Nested Records”, In: ACM Transactions on Storage, Vol. 15, No. 3, Article 16, 46 p. DOI: 10.1145/3321704.
34.“What are the pros and cons of using a columnar database for data mining? Are there any characteristics of the databases that can be used for deciding?” [Digital Resource]. – Available at: https://www.quora.com/What-are-the-pros-andcons-of-using-a-columnar-database-for-data-miningAre-there-any-characteristics-of-the-databases-thatcan-be-used-for-deciding. – Active link – 10 May 2020.
35. “What are the pros and cons of document and column-oriented databases?” [Digital Resource] – Available at: https://www.quora.com/What-are-thepros-and-cons-of-document-and-column-orienteddatabases. – Active link – 10 May 2020.
36. Bhagat, V. & Gopal, A. (2012). “Comparative Study of Row and Column Oriented Database”, In: 2012 Fifth International Conference on Emerging Trends in Engineering and Technology. DOI: 10.1109/icetet.2012.56.
37. Martins de Sousa, V. & Del Val Cura, L. M. (November 2018). “Logical Design of Graph Databases from an Entity-Relationship Conceptual Model”, In: Proceedings of the 20th International Conference on Information Integration and Web-Based Applications and Services, Yogyakarta, Indonesia, pp. 183-189. DOI: 10.1145/3282373.3282375.
38.“What are the pros and cons of using a graph database?” [Digital Resource]. – Available at: https://www.quora.com/What-are-the-pros-andcons-of-using-a-graph-database. – Active link – 10 May 2020.
39. Roopa Tangirala & Thomas Betts. (2018). “Polyglot Persistence Powering Microservices”. In: QCon San Francisco 2018 [Digital Resource]. – Available at: https://www.infoq.com/presentations/microservicespolyglot-persistence. – Active link – 10 May 2020.
40. Khine, P. P. & Wang, Z. (2019). “A Review of Polyglot Persistence in the Big Data World”, In: Information 2019, 10(4). DOI: 10.3390/info10040141.
41. Nazaruka, E. & Osis, J. (2018). “Determination of Natural Language Processing Tasks and Tools for Topological Functioning Modelling”, In: Proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering, Vol. 1: MDI4SE, pp. 501-512. DOI: 10.5220/0006817205010512.
42. Çığşar, B. & Ünal, D. (2019). “Comparison of Data Mining Classification Algorithms Determining the Default Risk”, In: Scientific Programming, Vol. 2019, pp. 1-8. DOI:10.1155/2019/8706505.
43. Harsh H. Patel & Purvi Prajapati, (2018). “Study and Analysis of Decision Tree Based Classification Algorithms”, International Journal of Computer Sciences and Engineering, 6(10), pp. 74-74. DOI: 10.26438/ijcse/v6i10.7478.
44. Maria G. Glava, Eugene V. Malakhov, Olena O. Arsiri & Borys F. Trofymov. (2019). “Information technology for combining the relational heterogeneous databases using an integration models of different subject domains”, Applied Aspects of Information Technology, Odessa, Ukraine, Publ, Science and Technical, Vol. 2 No. 1, pp. 29-44. DOI: 10.15276/aait.02.2019.3.
45. Müllenbach Sabine, Kern-Bausch Lore & Kolonko Matthias. (2019). “Conceptual Modeling Language Agila Mod”, Herald of Advanced Information Technology, Odessa, Ukraine, Publ, Science and Technical, Vol. 2, No. 4, pp. 246-258. DOI: 10.15276/hait.04.2019.1.
Received 05.05. 2020
Received after revision 10.06. 2020
Accepted 15.06. 2020
Vol. 3 № 2, 2020
22 Oct 2021
Search by author
Information Systems and Technologies
1. Models and Methods of Information Technology
2. Design of Information Systems and Technologies
3. Mathematical Issues of Information Technologies
4. Innovative Technologies in Education, Culture and art
5. Game Technologies, Augmented and Virtual Reality
6. Theoretical and Applied Issues of Computer Science
7. Project, Program and Portfolio Management
Digital control of Technical and Social Systems
1. Adaptive and optimal Control Systems
2. Parametric and System Identification
3. Interconnected Systems and Systems with Distributed Parameter
4. Renewable Energy Systems
5. Machine Learning and Artificial Intelligence in General Technical Problems and Electromechanics
6. Management of Production and Power Plants
7. Control Systems for Robotic Systems and Complexes, Electric Vehicles
8. Diagnosis and Evaluation of Complex Systems
9. Simulation of Physical Objects and Processes
Sensor less Control Systems
Software Engineering and Systems Analysis
1. Methods and Means of Intellectual Information Processing
2. Recognition, Decision Making, Forecasting
3. Neural Network Technologies and Machine Learning Methods
4. Semantic Models. Natural Language Processing
5. Theoretical and Applied Issues of Software Engineering
6. Models and Methods of Software Quality Management
Computer Systems and Cybersecurity
1. Parallel and Distributed Information Processing
2. Internet of Things
3. Information Security and Cybersecurity
4. Computer Networks and Systems
5. Components of Robotic Systems
KarelWintersky ] [
[ © Odessa National Polytechnic University, 2018.]