Pros of jackson-databind

• Higher-level API for data binding and object mapping
• Supports automatic serialization and deserialization of POJOs
• Offers advanced features like custom serializers/deserializers and annotations

Cons of jackson-databind

• Larger library size and potentially higher memory footprint
• Slightly slower performance due to additional abstraction layers
• More complex configuration for advanced use cases

Code Comparison

jackson-core (low-level streaming API):

JsonFactory factory = new JsonFactory();
JsonGenerator generator = factory.createGenerator(new File("output.json"));
generator.writeStartObject();
generator.writeStringField("name", "John");
generator.writeNumberField("age", 30);
generator.writeEndObject();
generator.close();

jackson-databind (high-level object mapping):

ObjectMapper mapper = new ObjectMapper();
Person person = new Person("John", 30);
mapper.writeValue(new File("output.json"), person);

jackson-databind builds upon jackson-core, providing a more convenient API for working with Java objects. While jackson-core offers fine-grained control over JSON parsing and generation, jackson-databind simplifies the process by automatically handling object serialization and deserialization. The trade-off is a larger library size and slightly reduced performance compared to the low-level API. Developers should choose based on their specific requirements for flexibility, ease of use, and performance.

Pros of gson

• Simpler API and easier to use for basic JSON operations
• Better performance for small JSON payloads
• More straightforward object mapping with less configuration

Cons of gson

• Less flexible for complex JSON structures
• Fewer features and customization options
• Limited support for streaming large JSON data

Code Comparison

jackson-core:

ObjectMapper mapper = new ObjectMapper();
MyObject obj = mapper.readValue(jsonString, MyObject.class);
String json = mapper.writeValueAsString(obj);

gson:

Gson gson = new Gson();
MyObject obj = gson.fromJson(jsonString, MyObject.class);
String json = gson.toJson(obj);

Both jackson-core and gson are popular Java libraries for JSON processing. jackson-core offers more advanced features and flexibility, making it suitable for complex JSON handling and high-performance scenarios. gson, on the other hand, provides a simpler API that's easier to use for basic JSON operations, making it a good choice for smaller projects or when simplicity is preferred over extensive customization options.

jackson-core excels in handling large JSON datasets and offers better streaming capabilities, while gson performs well with smaller payloads. The choice between the two often depends on the specific requirements of the project and the developer's familiarity with each library.

Pros of fastjson

• Generally faster parsing and serialization performance
• Supports more data types out of the box
• Simpler API for common use cases

Cons of fastjson

• Less mature and stable compared to jackson-core
• Fewer configuration options and customization features
• Limited support for advanced JSON features

Code Comparison

fastjson:

String jsonString = JSON.toJSONString(object);
MyObject obj = JSON.parseObject(jsonString, MyObject.class);

jackson-core:

ObjectMapper mapper = new ObjectMapper();
String jsonString = mapper.writeValueAsString(object);
MyObject obj = mapper.readValue(jsonString, MyObject.class);

Both libraries offer straightforward APIs for JSON serialization and deserialization. fastjson's API is slightly more concise, while jackson-core provides more flexibility through the ObjectMapper class.

fastjson is known for its high performance and ease of use, making it popular in scenarios where speed is crucial. However, jackson-core offers more robust features, better documentation, and wider community support, making it a more suitable choice for complex applications or those requiring extensive customization.

The choice between these libraries depends on specific project requirements, such as performance needs, feature set, and long-term maintainability.

Pros of json-iterator/java

• Faster parsing and serialization performance in many scenarios
• More memory-efficient, with lower allocation rates
• Supports non-blocking parsing for improved concurrency

Cons of json-iterator/java

• Less mature and widely adopted compared to jackson-core
• Smaller ecosystem and fewer third-party extensions
• May lack some advanced features present in jackson-core

Code Comparison

jackson-core:

ObjectMapper mapper = new ObjectMapper();
MyObject obj = mapper.readValue(jsonString, MyObject.class);
String json = mapper.writeValueAsString(obj);

json-iterator/java:

JsonIterator iter = JsonIterator.parse(jsonString);
MyObject obj = iter.read(MyObject.class);
String json = JsonStream.serialize(obj);

Both libraries offer similar functionality for parsing and serializing JSON, but json-iterator/java aims to provide better performance through its optimized parsing and serialization algorithms. However, jackson-core has a larger ecosystem and more extensive feature set, making it a more versatile choice for complex use cases. The choice between the two depends on specific project requirements, performance needs, and ecosystem considerations.

Pros of Moshi

• Designed specifically for Kotlin, offering better integration with Kotlin features
• Smaller library size and faster compilation times
• More straightforward API, making it easier to use for simpler projects

Cons of Moshi

• Less feature-rich compared to Jackson, with fewer data format supports
• Smaller community and ecosystem, potentially leading to fewer third-party extensions
• May require more manual configuration for complex serialization scenarios

Code Comparison

Jackson:

ObjectMapper mapper = new ObjectMapper();
MyObject obj = mapper.readValue(jsonString, MyObject.class);
String json = mapper.writeValueAsString(obj);

Moshi:

val moshi = Moshi.Builder().build()
val adapter = moshi.adapter(MyObject::class.java)
val obj = adapter.fromJson(jsonString)
val json = adapter.toJson(obj)

Both libraries offer similar functionality for JSON serialization and deserialization, but Moshi's API is more Kotlin-friendly. Jackson provides more extensive features and customization options, while Moshi focuses on simplicity and Kotlin integration. The choice between the two often depends on project requirements, existing ecosystem, and developer preferences.

Pros of JSON-java

• Simpler API with fewer dependencies, making it easier to use for small projects
• Lightweight and self-contained, suitable for environments with limited resources
• More straightforward parsing and generation of JSON data

Cons of JSON-java

• Less feature-rich compared to jackson-core, lacking advanced functionalities
• Lower performance for large-scale JSON processing tasks
• Limited support for custom serialization and deserialization

Code Comparison

JSON-java:

JSONObject obj = new JSONObject();
obj.put("name", "John");
obj.put("age", 30);
String jsonString = obj.toString();

jackson-core:

ObjectMapper mapper = new ObjectMapper();
ObjectNode obj = mapper.createObjectNode();
obj.put("name", "John");
obj.put("age", 30);
String jsonString = mapper.writeValueAsString(obj);

Both libraries allow for creating and manipulating JSON objects, but jackson-core offers more flexibility and advanced features through its ObjectMapper class. JSON-java provides a more straightforward approach with its JSONObject class, which may be preferable for simpler use cases.