Análise de desempenho das tecnologias de carregamento de dados em bancos de dados pela linguagem Java

Abstract

This work presents a comparative analysis of the main data persistence technologies used in Java applications: JDBC, Hibernate, JPA, and Spring Data JPA. Considering the growth in data volume and the need for increasingly efficient systems, it investigated how each technology influences performance, resource consumption, and development complexity. The research was guided by the following question: what are the advantages and disadvantages of each data manipulation approach in the context of modern Java applications? To answer this question, the study conducted a theoretical review of the different data access and persistence strategies, highlighting their technical characteristics, abstraction models, productivity, and impact on performance. Both low-level approaches, such as JDBC, and more abstract solutions, such as Hibernate, JPA, and Spring Data JPA, based on the ORM paradigm, which performs the mapping between Java language objects and relational database structures, were analyzed. The results indicate that JDBC offers greater control and raw performance, but requires more implementation and maintenance effort. ORM technologies, such as Hibernate and JPA, provide greater productivity and facilitate development, although they can introduce memory overflow and scalability problems in high-load scenarios. Spring Data JPA stands out for its simplicity and speed of development, but may suffer limitations when highly customized configurations or intensive operations are required. The analysis shows that the choice of the most appropriate technology depends directly on the application context, involving factors such as complexity of business logic, performance requirements, data volume, and the profile of the development team. It is concluded that no technology is universally superior, reinforcing the importance of well-founded architectural decisions. The study contributes to guiding professionals in selecting the most appropriate persistence approach and to fostering discussions about performance, scalability, and productivity in the Java ecosystem.