2026-04-17T16:01:11.316Z http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai

ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:2:8085 2023-06-08T14:38:52Z 2

Model driven development of hybrid databases using lightweight metamodel extensions 2018 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/2/8085 https://www.tandfonline.com/doi/abs/10.1080/17517575.2018.1445295 I. Zečević P. Bjeljac B. Perišić S. Stankovski D. Venus G. Ostojić The transition from traditional to Big Data technologies has put new challenges in front of existing database modelling techniques. The ‘Design then implement’ approach to relational database modelling, could not be fully applied to ‘Discover and analyze’ databases with rapid data growth. In the context of Big Data, models have preserved a descriptive role: they are used to analyze and understand the architecture of hybrid data structures. From the Model-Driven Engineering point of view, several questions emerge: Could Big Data and hybrid database models represent a formal specification for a solution, which can be transformed to an executable specification for a specific target platform? Does the refining mechanism have its place in the process of hybrid data structure development? An approach to modelling hybrid databases, based on empirically validated concepts of Model-Driven Engineering, is presented article https://doi.org/10.1080/17517575.2018.1445295 12 8-9 1221 1238 1751-7583 Enterprise Information Systems, Taylor & Francis