Oliveira, Luiz Affonso Henderson Guedes deCavalcante, Ana Rute da Silva2022-07-262022-07-262022-07-15CAVALCANTE, Ana Rute da Silva. Análise de desempenho entre as linguagens Java e Scala. 2022. 67f. Trabalho de Conclusão de Curso (Graduação em Engenharia de Computação) - Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2022.https://repositorio.ufrn.br/handle/123456789/48733We currently live in an era known as the "Era of Social Media", where information of all kinds is generated and consumed by almost always complex applications every second, with the extreme need for almost instantaneous processing. This is an example of what is known as Big Data. Big Data refers to the large amount of data in constant motion and the operations on it. Applications such as the Internet of Things, Artificial Intelligence, mobile applications, sensors, banking transactions, and even e-commerce, as well as the social networks mentioned above, are some examples of how we can feel the impact of Big Data in our daily lives. For this, some technologies and tools had to be created or adapted to deal with the growth of Big Data. Among them, there are Java and Scala, our objects of study. The main objective of this work is to present and study the Java and Scala languages, their main features and code structures, as well as analyze their behavior through time measurements and graphing in simulations of Big Data applications. The results were collected from the execution of programs developed in Java and Scala, as well as, for comparative purposes, also using the Spark framework, a technology that also supports Big Data applications. At the end of this dissertation, it is expected that the reader will be able to have a good conception of the main advantages and disadvantages of working with these languages, and for what type of application they are better.Attribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/ScalaJavaBig DataSparkProcessamento de dadosData ProcessingbachelorThesis