Issues and Prospects of Integrating Relational Databases with Cloud Technologies

  • Vladyslav Kozub Department of Information Technology and Systems, Luhansk Taras Shevchenko National University, Poltava, Ukraine. https://orcid.org/0000-0003-2710-7206
  • Sergii Bataiev Department of Technology, the University of Warwick, ELEKS inc., Lviv, Ukraine. https://orcid.org/0009-0009-9564-9403
  • Oksana Shybko Department of Computer Science, Information Technology and Applied Mathematics, Faculty of Information Technology and Mechanical Engineering, Ukrainian State University of Science and Technologies, SEI ‘Prydniprovska State Academy of Civil Engineering and Architecture’, Dnipro, Ukraine. https://orcid.org/0000-0001-5894-0642
  • Yaroslava Sikora Department of Computer Science and Information Technology, Faculty of Physics and Mathematics, Zhytomyr Ivan Franko State University, Zhytomyr, Ukraine. https://orcid.org/0000-0003-2621-6638
  • Serhii Voloshchuk Department of Modelling of Complex Systems, Faculty of Computer Science and Cybernetics, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine. https://orcid.org/0009-0000-6416-5566

Abstract

Relevance. The integration of relational databases into cloud computing environments is characterized by the rapid growth of data volumes, the need to ensure flexibility, scalability and high performance of information management systems. Given that cloud technologies allow organizations to quickly adapt infrastructure to changing loads, integrate transactional and analytical processes, increase the efficiency of business processes and minimize operating costs; integration of RDBMS with cloud services is becoming a key factor in ensuring sustainability, security and competitiveness of organizations.

Objective. The purpose of this article is to systematically analyze the current challenges of integrating relational databases into cloud computing environments and to identify promising areas for their development, considering technological and organizational aspects.

Methods. The study applies to a set of methods that provides a systematic and reasonable assessment of the integration of relational databases into cloud environments. The forecasting method was used to outline the market prospects and growth dynamics of corporate data in the cloud; methods of synthesis, systematization and generalization were used to classify architectural models, analyze technical, economic and security aspects and identify key development trends; and a comparative analysis of cases of leading cloud RDBMS providers allowed to assess the effectiveness of real implementation; which provides a holistic view of the problem and forms a methodological basis for a reasonable choice of integration models.

Results. According to the report, the amount of enterprise data being stored in the cloud is increasing in tandem with the steady growth of the global cloud computing market. This demonstrates the importance of cloud solutions for strategic planning and the speed at which businesses are digitizing. Cloud-native, hybrid, multi-cloud, and microservice models that offer cost-effectiveness, technical agility, and security are all options for relational database integration into the cloud. AI-driven management, serverless architectures, and containerization all boost productivity by enabling real-time data flow optimization.

Conclusions. It is suggested that a successful integration approach for RDBs into the cloud can be established based on adaptability (flexibility), autonomy, and interoperability, ensuring strategic flexibility of organizations. Leveraging data fabric, data mesh, and autonomous AI-driven solutions, classic management logic is transformed from one of reactive administration to one of proactive load prediction. This multi-dimensional strategy drives digital transformation efficiency and forms the competitive capabilities of today’s enterprises.

 

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Published
2026-04-28
How to Cite
Kozub, V., Bataiev, S., Shybko, O., Sikora, Y., & Voloshchuk, S. (2026). Issues and Prospects of Integrating Relational Databases with Cloud Technologies. ITEGAM-JETIA, 12(58), 1427-1435. https://doi.org/10.5935/jetia.v12i58.3380
Section
Articles