Ring Buffers vs. Double-Ended Linked Lists

Ring Buffers vs. Double-Ended Linked Lists

When it comes to computer programming, data structures are essential building blocks. Among the variety, ring buffers and double-ended linked lists stand out with their unique features, implementations, and use cases. Let’s take a closer look at what sets them apart:

Ring Buffers: A Circular Dance

Ring buffers, also known as circular or cyclic buffers, are fixed-size data structures where memory connects end-to-end, forming a loop. They’re perfect for buffering data, especially when there’s a producer-consumer dynamic with fluctuating data production and consumption rates.

Some key features of ring buffers include:

1. Fixed-size: The buffer’s size is determined during creation and remains constant.
2. Overwriting: When the buffer is full and new data arrives, the oldest data is overwritten.
3. Efficient: Adding and removing elements is typically fast since it only involves updating pointers without memory allocation or deallocation.

Double-Ended Linked Lists: The Two-Way Street

On the other hand, double-ended, or doubly linked lists, are data structures where each element (node) holds data and two pointers—one pointing to the previous node and the other to the next node in the sequence. This design allows efficient traversal in both directions. A double-ended linked list has a front (head) and a back (tail), streamlining insertion and removal at both ends.

Key features of double-ended linked lists include:

1. Dynamic size: The list’s size can change during its lifetime, as elements are added or removed.
2. No overwriting: Instead of overwriting data, new nodes are created or deleted as needed.
3. Slower than ring buffers: Adding and removing elements may be slower than in ring buffers, as memory allocation and deallocation might be involved.

Our Usecase

Recently we needed a fast fixed size storage to keep track of recent activities. Our primary concern was achieving swift performance and minimal latency. With these goals in mind, we opted for the following implementation to reach the high throughput we desired:

A Simple Golang Implementation Of Ring Buffer

type CircularBuffer[T any] struct {
	buffer []T
	size   int
	head   int
	tail   int
	count  int
	mu     sync.RWMutex
}

// NewCircularBuffer constructor
func New[T any](size int) *CircularBuffer[T] {
	return &CircularBuffer[T]{
		buffer: make([]T, size),
		size:   size,
		head:   0,
		tail:   0,
		count:  0,
	}
}

// Add new item to the circular buffer's tail
func (cb *CircularBuffer[T]) Add(item T) {
	cb.mu.Lock()
	defer cb.mu.Unlock()

	cb.buffer[cb.tail] = item
	cb.tail = (cb.tail + 1) % cb.size

	if cb.count < cb.size {
		cb.count++
	} else {
		cb.head = (cb.head + 1) % cb.size
	}
}

// GetRecent items from the buffer
func (cb *CircularBuffer[T]) GetRecent(count int) []T {
	cb.mu.RLock()
	defer cb.mu.RUnlock()

	result := make([]T, 0, count)
	elements := 0
	startIndex := (cb.tail - 1 + cb.size) % cb.size

	for i := startIndex; elements < count && elements < cb.count; i = (i - 1 + cb.size) % cb.size {
		result = append(result, cb.buffer[i])
		elements++
	}
	return result
}

The Bottom Line

The main distinction between ring buffers and double-ended linked lists lies in their implementation and use cases. Ring buffers are fixed-size, efficient data structures ideal for buffering, while double-ended linked lists offer dynamic sizing and greater flexibility, albeit with potentially slower operations.