Pros of concurrentqueue

• More feature-rich, offering multiple queue types (MPMC, SPSC, MPSC)
• Generally higher performance, especially for high-contention scenarios
• Extensive documentation and benchmarks provided

Cons of concurrentqueue

• More complex implementation, potentially harder to understand and maintain
• Larger codebase and memory footprint
• May have higher overhead for simple use cases

Code Comparison

MPMCQueue:

template <typename T>
class MPMCQueue {
public:
  explicit MPMCQueue(const size_t capacity);
  bool try_push(const T &value);
  bool try_pop(T &value);
};

concurrentqueue:

template<typename T, size_t MAX_SUBQUEUES = 32>
class ConcurrentQueue {
public:
  ConcurrentQueue();
  void enqueue(T element);
  bool try_dequeue(T& element);
  size_t size_approx() const;
};

Key Differences

• MPMCQueue is specifically designed for multi-producer, multi-consumer scenarios, while concurrentqueue offers more queue types
• concurrentqueue provides additional features like bulk operations and implicit sizing
• MPMCQueue has a simpler API, focusing on core push/pop operations
• concurrentqueue uses more advanced techniques for lock-free implementation, potentially offering better scalability

Both libraries are well-suited for concurrent programming, but concurrentqueue may be preferred for more complex scenarios or when higher performance is crucial, while MPMCQueue might be a better choice for simpler use cases or when a smaller, more focused implementation is desired.

Pros of Folly

• Comprehensive C++ library with a wide range of utilities and components
• Actively maintained by Facebook with frequent updates and improvements
• Extensive documentation and examples available

Cons of Folly

• Large codebase with many dependencies, potentially increasing build times
• May include unnecessary components for projects only needing a queue implementation
• Steeper learning curve due to the breadth of features

Code Comparison

MPMCQueue:

MPMCQueue<int> q(100);
q.push(42);
int value;
q.pop(value);

Folly:

folly::MPMCQueue<int> q(100);
q.write(42);
int value;
q.read(value);

Summary

MPMCQueue is a focused, single-purpose implementation of a multi-producer multi-consumer queue. It's lightweight and easy to integrate into projects. Folly, on the other hand, is a comprehensive C++ library that includes an MPMC queue implementation along with many other utilities. While Folly offers more features and ongoing support from Facebook, it may be overkill for projects only needing a queue. The choice between the two depends on project requirements and the desire for a minimal vs. feature-rich solution.

Pros of Junction

• Offers a wider variety of concurrent data structures (queues, maps, tuples)
• Provides more flexibility with customizable memory allocation and reclamation strategies
• Supports multiple platforms including Windows, Linux, and macOS

Cons of Junction

• May have higher memory overhead due to its more complex implementation
• Potentially slower performance for simple use cases compared to MPMCQueue's focused design
• Less frequently updated, with the last major update being several years ago

Code Comparison

MPMCQueue:

MPMCQueue<int> q(100);
q.push(42);
int value;
q.pop(value);

Junction:

junction::ConcurrentMap_Leapfrog<int, int> map;
map.assign(42, 100);
int value = map.get(42);

Summary

MPMCQueue is a focused, high-performance multi-producer multi-consumer queue implementation, while Junction offers a broader range of concurrent data structures with more customization options. MPMCQueue may be preferable for simpler use cases requiring maximum performance, while Junction provides more flexibility for complex concurrent programming scenarios across multiple platforms.

Pros of atomic_queue

• Generally faster performance, especially for high-concurrency scenarios
• More memory-efficient, using less memory per queue element
• Supports both bounded and unbounded queue implementations

Cons of atomic_queue

• Less mature project with potentially fewer real-world deployments
• Documentation is not as comprehensive as MPMCQueue
• May have less robust error handling and edge case coverage

Code Comparison

MPMCQueue:

template <typename T>
class MPMCQueue {
public:
  explicit MPMCQueue(const size_t capacity);
  bool try_push(const T &value);
  bool try_pop(T &value);
};

atomic_queue:

template <typename T, unsigned N>
class atomic_queue {
public:
  atomic_queue() = default;
  bool try_push(T element);
  bool try_pop(T& element);
};

Both implementations offer similar core functionality with try_push and try_pop methods. However, atomic_queue uses a template parameter for queue size, while MPMCQueue uses a constructor parameter. This difference reflects atomic_queue's focus on compile-time optimizations.

atomic_queue provides a more diverse set of queue implementations, including bounded and unbounded variants, which may offer better performance in specific use cases. MPMCQueue, on the other hand, focuses on a single, well-tested implementation that may be more suitable for general-purpose use in production environments.

Pros of libcds

• Offers a wider range of concurrent data structures beyond just queues
• Provides more flexibility with various implementation options for each data structure
• Supports both C++11 and C++14 standards

Cons of libcds

• More complex API due to its broader scope and flexibility
• Potentially higher learning curve for developers new to the library
• May have slightly higher overhead due to its generalized approach

Code Comparison

MPMCQueue:

MPMCQueue<int> q(100);
q.push(42);
int value;
q.pop(value);

libcds:

cds::container::MSQueue<cds::gc::HP, int> q;
q.enqueue(42);
int value;
q.dequeue(value);

Summary

MPMCQueue is a focused, single-purpose library for multi-producer/multi-consumer queues, while libcds is a comprehensive concurrent data structures library. MPMCQueue may be simpler to use for specific queue implementations, but libcds offers more versatility for various concurrent data structure needs. The choice between them depends on the project requirements and the developer's familiarity with concurrent programming concepts.