How span is different than list in C#

Question

How is Span different from List , and which one is best for performance?

Rinki · Answer

List is a resizable collection that lives on the heap, making it ideal for situations where you need to frequently add or remove items. It provides rich functionality but involves more memory overhead and garbage collection. Span , on the other hand, is a fixed-size, stack-allocated view over existing memory, offering high performance with minimal allocations. It's great for scenarios requiring efficient memory access without resizing, like array slicing or handling fixed buffers. In short, use List for flexibility and dynamic growth, and Span for speed and low-level memory operations.

Aman Gupta · Answer

Hi Shivam, Span and List are two data structures in .NET, but they serve different purposes and have different characteristics, especially in terms of performance and memory management . Below, I’ll explain the differences and give insights into which is better for performance, depending on the use case. 1. Memory Management: Span : Span is a stack-only structure that provides a view over a contiguous block of memory (such as an array, memory from the stack, or a portion of an existing array). It does not own the memory but rather operates over existing memory, meaning it does not allocate memory on the heap. Span is lightweight and efficient because it doesn't involve allocations or resizing, and it is used for scenarios where you need to work with slices of arrays or memory buffers without making copies. List : List is a heap-allocated collection that dynamically manages a resizable array under the hood. It manages its own memory by growing the internal array as needed when new items are added, which incurs allocation and copy costs. List has a lot of flexibility in terms of adding, removing, and accessing elements, but this comes with overhead due to heap allocations and resizing. 2. Mutability and Resizing: Span : Span cannot be resized. It represents a fixed-size view over existing memory. You cannot add or remove elements from a Span , only modify the elements within the given range. If you need to add or remove elements dynamically, Span is not suitable, but it excels in scenarios where the size is fixed and known in advance. List : List is dynamically resizable, making it convenient for scenarios where the number of elements is unknown or changes frequently. However, resizing comes with performance costs, as it requires allocating a new array and copying over the elements whenever the capacity of the list is exceeded. 3. Performance: Span : Faster for fixed-size data manipulation : Since Span avoids heap allocations and runs directly on existing memory, it can be faster than List for operations like slicing arrays or working with buffers. Minimal overhead : Because Span is designed to work with stack-allocated data or fixed-length buffers, there is virtually no memory overhead, making it more efficient for memory-constrained operations. Ideal for scenarios where the performance of accessing and manipulating in-memory data is critical (e.g., high-performance applications like games, parsers, or real-time systems). List : More overhead due to dynamic resizing : Each time List grows beyond its current capacity, it has to allocate a larger array and copy elements, which impacts performance, especially in scenarios with frequent additions. Despite these costs, List is still performant for general use cases where dynamic size changes are necessary, and the slight performance overhead is acceptable. Access to elements in a List (indexer-based access) is very fast (O(1) time complexity), but modifications that require resizing (like Add , Remove ) can incur extra costs. 4. Use Cases: Span : High-performance scenarios : Span is designed for performance-critical code, such as working with buffers, memory manipulation, or slices of arrays where dynamic allocation and copying should be avoided. Memory-efficient processing : If you're working with large datasets (e.g., image processing, networking buffers) where you just need to process data and not store it permanently, Span is a good choice. Fixed-size operations : If you have data that won’t change in size (e.g., you’re reading data into an array and just want to operate on parts of it), Span is perfect. List : Dynamic collection handling : List is great when you need to manage a collection whose size changes over time. It’s ideal for situations where elements are frequently added or removed. General-purpose collection : List is a high-level data structure that offers a lot of functionality out of the box, such as sorting, searching, and collection-wide operations like ForEach . Higher-level use cases : If performance isn’t the absolute top priority and you need a flexible collection that grows and shrinks, List is the better choice. 5. Memory Safety and Stack Limitations: Span : Span operates on stack memory, so it's constrained by the stack size of the thread. Stack sizes are typically much smaller than heap sizes, so you can't store large data in Span . However, Span can also reference heap-allocated arrays without copying them. But for stack-allocated spans (like stackalloc ), large allocations can lead to stack overflow exceptions. List : Since List is heap-allocated, it is not constrained by the stack size. You can store significantly larger amounts of data in a List , although at the cost of dynamic memory management. 6. Safety and Lifetime Constraints: Span : Lifespan constraints : Span is meant to be short-lived and cannot be stored on the heap, which limits its use outside of local scopes. Stack safety : You can't return a Span from a method if it's referencing stack-allocated memory, as that memory would no longer be valid once the method returns. List : No such lifespan restrictions exist for List , as it’s stored on the heap. This makes it easier to pass between methods and store in class fields. 7. Summary of Differences: Aspect Span List Memory Allocation Stack-allocated or a slice of existing memory Heap-allocated, dynamically resizable array Resizing Fixed-size (non-resizable) Dynamically resizable Performance Faster for fixed-size, in-memory operations Slower due to resizing and heap allocations Use Cases High-performance scenarios, low-level memory access General-purpose dynamic collections Context Short-lived, stack-constrained Long-lived, heap-allocated Memory Safety Stack-safe, cannot be heap-allocated No stack constraints, heap-based Thread Safety Can be used safely for memory slices Not inherently thread-safe without synchronization When to Choose Each: Choose Span : If you are working with slices of memory or arrays and need maximum performance with minimal memory overhead. If you know the size of the data and don’t need the collection to grow or shrink dynamically. For high-performance applications (e.g., parsers, network buffers, game engines). Choose List : If you need a dynamic, resizable collection where elements will be added and removed frequently. If you need the convenience of built-in operations like searching, sorting, and enumerating. For general-purpose applications where performance is important but not absolutely critical. Conclusion: For performance-critical operations involving fixed-size memory manipulation, Span offers significant advantages because it avoids the overhead of heap allocations and resizes. However, if you need flexibility with a dynamic collection, List is more appropriate, even though it has additional overhead.

Muhammad Imran Ansari · Answer

Hi Shivam, Both are used to manage collections of data, but they serve different purposes depending on the scenario and requirements. Below are some characteristics to help determine which is more appropriate for your specific use case: List Span Memory dynamically-sized collection. It allocates memory on the managed heap and can grow or shrink as needed. fixed in size. This is memory-efficient due to stack-allocated memory Usage Designed or useful for managing collections that need to be resized, inserted, or modified over time (dynamically) Useful when working with pre-defined size or existing data (e.g., arrays, strings, buffers). Resizing Automatically resizes when items are added fixed in size. It cannot be resized automatically Performance Since it is dynamically resizable and allocated on the heap, operations like resizing can introduce performance overhead. It is more efficient for short-lived Lifetime It is managed by the garbage collector. You can keep it alive as long as you need it. It is a stack-only construct so it has a shorter lifetime and must remain within the scope where it is defined. Mutability Allows insertion, removal, and modification of elements at any time. Allows modifying the data it refers to but it does not allow resizing or managing the underlying memory. Safety and Constraints It is type-safe and does not expose direct memory manipulation. It is also type-safe, but it’s more low-level. Thank you. Happy Coding!