Pros of Dozer

• More configurable and flexible, allowing for complex mappings
• Supports XML-based configuration for mapping rules
• Better performance for large-scale mapping operations

Cons of Dozer

• Steeper learning curve due to more complex configuration options
• Requires more setup and boilerplate code for simple mappings
• Less active development and community support compared to ModelMapper

Code Comparison

Dozer:

Mapper mapper = DozerBeanMapperBuilder.buildDefault();
DestinationObject destObject = mapper.map(sourceObject, DestinationObject.class);

ModelMapper:

ModelMapper modelMapper = new ModelMapper();
DestinationObject destObject = modelMapper.map(sourceObject, DestinationObject.class);

Both libraries provide similar basic mapping functionality, but Dozer offers more advanced configuration options for complex scenarios. ModelMapper, on the other hand, focuses on simplicity and convention-based mapping.

Dozer excels in scenarios requiring intricate mapping rules and high performance for large datasets. ModelMapper is more suitable for projects prioritizing ease of use and quick setup, especially for simpler mapping requirements.

The choice between the two depends on the specific needs of the project, with Dozer being more powerful but complex, and ModelMapper offering a more straightforward approach for common use cases.

Pros of Orika

• Generally faster performance, especially for large-scale mapping operations
• More flexible configuration options for complex mapping scenarios
• Built-in support for multi-threaded mapping

Cons of Orika

• Steeper learning curve due to more complex API
• Requires more setup and configuration compared to ModelMapper
• Less active development and community support

Code Comparison

ModelMapper:

modelMapper.createTypeMap(Source.class, Destination.class)
    .addMappings(mapper -> {
        mapper.map(Source::getFirstName, Destination::setName);
        mapper.map(Source::getAge, Destination::setYears);
    });

Orika:

mapperFactory.classMap(Source.class, Destination.class)
    .field("firstName", "name")
    .field("age", "years")
    .register();

Both ModelMapper and Orika are popular Java object mapping libraries. ModelMapper focuses on simplicity and convention-based mapping, making it easier to use for straightforward scenarios. Orika, on the other hand, offers more powerful features and better performance at the cost of increased complexity. The choice between the two depends on the specific requirements of your project, such as performance needs, mapping complexity, and development team expertise.

Pros of MapStruct

• Compile-time code generation, resulting in faster execution and earlier error detection
• Type-safe mapping with minimal runtime overhead
• Extensive customization options through annotations and custom mapping methods

Cons of MapStruct

• Steeper learning curve due to annotation-based configuration
• Requires an additional build step for code generation
• Less flexibility for dynamic mapping scenarios at runtime

Code Comparison

MapStruct:

@Mapper
public interface CarMapper {
    @Mapping(source = "numberOfSeats", target = "seatCount")
    CarDto carToCarDto(Car car);
}

ModelMapper:

ModelMapper modelMapper = new ModelMapper();
CarDto carDto = modelMapper.map(car, CarDto.class);

MapStruct generates type-safe mapping code at compile-time, while ModelMapper performs reflection-based mapping at runtime. MapStruct offers better performance and earlier error detection, but ModelMapper provides more flexibility for dynamic mappings without additional build steps.

Both libraries have their strengths, and the choice depends on project requirements, performance needs, and developer preferences. MapStruct is ideal for large-scale projects with complex mapping requirements, while ModelMapper excels in rapid prototyping and scenarios requiring runtime flexibility.