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Can someone please explain what the main differences between these two data structures are? I've been trying to find a source online that highlights the differences/similarities, but I haven't found anything too informative. In what cases would one be preferred over the other? What practical situations make one "better" to use than the other?
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AVL trees provide complex insertion and removal operations as more rotations are done due to relatively relaxed balancing. Red Black Tree requires only 1 bit of information per node. AVL trees store balance factors or heights with each node thus requiring storage for an integer per node.
The complexity of tree operation in the red-black tree data structure is the same as the AVL tree. The red-black tree is a self-balancing binary search tree with the same complexity as the AVL tree.
In Binary Search tree, the height or depth of the tree is O(n) where n is the number of nodes in the Binary Search tree. In AVL tree, the height or depth of the tree is O(logn). It is simple to implement as we have to follow the Binary Search properties to insert the node.
AVL trees maintain a more rigid balance than red-black trees. The path from the root to the deepest leaf in an AVL tree is at most ~1.44 lg(n+2), while in red black trees it's at most ~2 lg (n+1).
As a result, lookup in an AVL tree is typically faster, but this comes at the cost of slower insertion and deletion due to more rotation operations. So use an AVL tree if you expect the number of lookups to dominate the number of updates to the tree.
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