The average case time for lookup in a binary search tree, treap and 2-3 tree is O(log n) and in unordered lists it is O(n). But in the worst case, only the 2-3 trees perform lookup efficiently as it takes O(log n), while others take O(n).
Search is more efficient in the 2-3 tree than in BST. 2-3 tree is a balanced tree and performs efficient insertion and deletion and it is shallower than BST. But, 2-3 tree requires more storage than the BST.
The number of elements in a 2-3 tree with height h is between 2h – 1 and 3h – 1. Therefore, the 2-3 tree with n elements will have the height between log3(n + 1) and log2(n + 1).
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Compression techniques can be used on the keys to reduce both space and time requirements in a B-tree.
The front compression and the rear compression are techniques used to reduce space and time requirements in B-tree. The compression enables to retain more keys in a node so that the number of nodes needed can be reduced.
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