Paper Title
Optimizing Query Processing Through Application of Hybrid Json-Relational Data Model

Abstract
Legacy database applications often require efficient data retrieval and manipulation, prompting the need for database improvements. Traditional relational databases, while robust, can sometimes hinder performance for complex queries, especially those involving multiple joins. As data volumes and complexities of applications grow, the need to reduce the data retrieval time becomes increasingly critical. In this work, we address the problem of data model transformation from the relational model into a hybrid JSON-relational model to improve database performance. The motivation is derived from the need to modernize existing systems to meet the demands of today's dynamic data environments. To address this problem, we propose a series of algorithms designed to transform a relational data model into a hybrid JSON-relational data model. This model transformation is controlled by the characteristics of a given collection of applications by eliminating costly operations on the database. We primarily focus on database applications that require computation of join operations. The estimation of the performance of applications over the new database structure offers some positive results. Keywords - Relational Data Model, JSON-Relational Data Model, Nested Data Model