How do different tree structures compare in performance?

How do different tree structures compare in performance?

Different tree structures, like binary trees, AVL trees, and B-trees, have varying performance based on operations like insertion, deletion, and search. For instance, AVL trees provide faster lookups due to their balanced nature, while B-trees are optimized for disk storage.

What are the advantages of using a B-tree over a binary tree?

B-trees are more efficient for large datasets as they minimize disk reads and writes. They maintain balance and allow for more keys per node, which reduces the height of the tree, leading to faster search times.

Can you explain how AVL trees maintain balance?

AVL trees maintain balance by ensuring that the heights of the two child subtrees of any node differ by no more than one. When an insertion or deletion causes this balance to be violated, rotations are performed to restore it.

What scenarios would you recommend using a binary search tree?

Binary search trees are suitable for scenarios where data is frequently inserted and deleted, and the dataset is relatively small. They are simple to implement and can be efficient if balanced.