Pros of fmt

• Focused on string formatting and output, providing a more intuitive and type-safe alternative to printf
• Header-only library, making it easy to integrate into projects
• Supports a wide range of formatting options and custom types

Cons of fmt

• Limited to string formatting and output, not a general-purpose serialization solution
• May have slightly higher compile times due to heavy template usage
• Requires C++11 or later, which might be an issue for older codebases

Code Comparison

fmt:

#include <fmt/core.h>
std::string result = fmt::format("Hello, {}!", "world");
fmt::print("The answer is {}.", 42);

FlatBuffers:

#include "monster_generated.h"
flatbuffers::FlatBufferBuilder builder;
auto name = builder.CreateString("Orc");
auto monster = CreateMonster(builder, name, 0, 300);
builder.Finish(monster);

Summary

fmt is a powerful string formatting library, while FlatBuffers is a serialization system. They serve different purposes, with fmt excelling in text output and FlatBuffers focusing on efficient data serialization. Choose fmt for string manipulation and formatting, and FlatBuffers for cross-platform data exchange and storage.

Pros of Protocol Buffers

• More mature and widely adopted, with extensive language support
• Built-in support for backwards compatibility and schema evolution
• Smaller message sizes for complex data structures with many optional fields

Cons of Protocol Buffers

• Slower serialization and deserialization compared to FlatBuffers
• Requires parsing the entire message before accessing any data
• Larger binary size due to additional runtime library

Code Comparison

Protocol Buffers:

message Person {
  required string name = 1;
  optional int32 age = 2;
  repeated string hobbies = 3;
}

FlatBuffers:

table Person {
  name:string;
  age:int32;
  hobbies:[string];
}

Both examples define a simple Person structure with similar fields. Protocol Buffers uses keywords like required, optional, and repeated, while FlatBuffers uses a more straightforward table definition.

FlatBuffers offers zero-copy deserialization, allowing direct access to data without parsing the entire message. This results in faster performance for large datasets or when only partial data access is needed. However, Protocol Buffers provides better support for schema evolution and backwards compatibility, making it more suitable for systems with frequently changing data structures or long-term data storage requirements.

Pros of msgpack-c

• Simpler and more lightweight serialization format
• Wider language support and ecosystem
• Faster serialization and deserialization for small data structures

Cons of msgpack-c

• Less efficient for larger, more complex data structures
• Lacks built-in schema evolution and backwards compatibility features
• No direct support for zero-copy reads

Code Comparison

msgpack-c:

msgpack_pack_array(&pk, 3);
msgpack_pack_int(&pk, 1);
msgpack_pack_true(&pk);
msgpack_pack_str(&pk, 5);
msgpack_pack_str_body(&pk, "Hello", 5);

FlatBuffers:

auto name = builder.CreateString("Hello");
auto monster = CreateMonster(builder, 1, true, name);
builder.Finish(monster);

FlatBuffers requires a schema definition and generates code, while msgpack-c uses a more dynamic approach. FlatBuffers offers stronger typing and better performance for larger datasets, but msgpack-c is simpler for small, dynamic data structures.

Both libraries are widely used and have their strengths. FlatBuffers excels in scenarios requiring high performance and schema evolution, while msgpack-c is more suitable for simpler, lightweight serialization needs across multiple languages.

Pros of Cap'n Proto

• Zero-copy deserialization, resulting in faster parsing
• Built-in RPC system for distributed computing
• More expressive schema language with advanced features like generics

Cons of Cap'n Proto

• Larger message size due to padding and alignment requirements
• Steeper learning curve and more complex API
• Less widespread adoption compared to FlatBuffers

Code Comparison

Cap'n Proto schema:

struct Person {
  name @0 :Text;
  age @1 :UInt32;
  address @2 :Address;
}

FlatBuffers schema:

table Person {
  name:string;
  age:uint32;
  address:Address;
}

Both Cap'n Proto and FlatBuffers offer efficient serialization formats for structured data. Cap'n Proto excels in scenarios requiring zero-copy deserialization and distributed computing, while FlatBuffers provides a simpler API and smaller message sizes. The choice between them depends on specific project requirements, such as performance needs, message size constraints, and desired features like RPC support.

Pros of Thrift

• Supports more programming languages than FlatBuffers
• Provides built-in RPC (Remote Procedure Call) functionality
• Offers a more mature ecosystem with broader adoption

Cons of Thrift

• Generally slower serialization and deserialization compared to FlatBuffers
• Larger message sizes, especially for small data structures
• Requires full parsing of data before accessing any fields

Code Comparison

Thrift IDL:

struct Person {
  1: string name
  2: i32 age
  3: string email
}

FlatBuffers IDL:

table Person {
  name:string;
  age:int32;
  email:string;
}

Both IDLs define a simple Person structure with similar fields. The main difference is in syntax and how the fields are numbered (Thrift) or not (FlatBuffers).

FlatBuffers allows for zero-copy deserialization and direct access to fields without parsing the entire message, which can lead to performance benefits in certain scenarios. Thrift, on the other hand, offers more language support and built-in RPC capabilities, making it potentially more suitable for complex distributed systems.

Pros of json

• Easier to read and write JSON data directly
• Wider language support and ecosystem
• More flexible for dynamic data structures

Cons of json

• Slower parsing and serialization
• Larger data size, especially for numeric values
• Less type safety compared to strongly-typed schemas

Code Comparison

json:

#include <nlohmann/json.hpp>
using json = nlohmann::json;

json j = {
  {"name", "John"},
  {"age", 30},
  {"city", "New York"}
};
std::string serialized = j.dump();

FlatBuffers:

#include "person_generated.h"
flatbuffers::FlatBufferBuilder builder;
auto name = builder.CreateString("John");
auto person = CreatePerson(builder, name, 30, "New York");
builder.Finish(person);
uint8_t *buf = builder.GetBufferPointer();

FlatBuffers requires a schema definition and code generation, while json allows for more dynamic data manipulation. FlatBuffers offers better performance and smaller data size, but at the cost of flexibility and ease of use. The choice between the two depends on specific project requirements, such as performance needs, data structure complexity, and development workflow preferences.