In any web service that receives and transmits data to and from a server, the first and last events will usually be transforming the data from the format used by the web request into the format that the web server will handle, and vice versa; these operations are called deserialization and serialization, respectively. For some web services, the thought put towards this part of the flow of data is focused solely on how to configure the serialization mechanism so it works properly. However, there are some scenarios for which every CPU cycle counts, and the faster the serialization mechanism can work, the better. This article will explore the development and performance characteristics of four different options for working with the serialization of JSON messages—GSON, Jackson, JSON-B, and Kotlinx Serialization, using both the Kotlin programming language and some of the unique features that Kotlin offers compared to its counterpart language, Java.
Setup
Since its first release in 2017, Kotlin has grown by leaps and bounds within the JVM community, becoming the go-to programming language for Android development as well as a first-class citizen in major JVM tools like Spring, JUnit, Gradle, and more. Among the innovations it brought to the JVM community compared to Java was the data class, a special type of class that is to be used primarily as a holder of data (in other words, a Data Transfer Object, or DTO) and automatically generates base utility functions for the class like equals(), hashcode(), copy(), and more. This will form the base of the classes that will be used for the performance tests, the first of which being PojoFoo. “Pojo” stands for “Plain Old Java Object,” signifying using only basic class types of the Java programming language: