What Is Balanced Binary Search Tree in Data Structure?


Scott Campbell

A balanced binary search tree is a type of data structure that organizes elements in a hierarchical manner. It is specifically designed to provide efficient search, insert, and delete operations. In this article, we will explore the concept of balanced binary search trees and understand why they are crucial in certain applications.

What is a Binary Search Tree?

A binary search tree (BST) is a type of binary tree where each node has at most two children: a left child and a right child. The BST property states that for any node, all the elements in its left subtree are smaller than the node’s value, and all the elements in its right subtree are greater than the node’s value.

Here’s an example of a binary search tree:

         /  \
        5    15
       / \   / \
      3   7 12  20

The Need for Balance

In some cases, if we perform multiple insertions or deletions on a BST with specific input orderings, it can lead to an unbalanced tree. An unbalanced tree can cause inefficient search and retrieval operations since the height of the tree increases significantly.

To overcome this issue, balanced binary search trees were introduced. A balanced BST ensures that the height of the tree remains relatively small compared to the number of elements stored. This balance allows for efficient operations and reduces time complexity.

Types of Balanced Binary Search Trees

There are various types of balanced binary search trees available. Some commonly used ones include:

  • AVL Trees: AVL trees were one of the first self-balancing BSTs invented by Adelson-Velsky and Landis. They maintain balance by performing rotations whenever necessary.
  • Red-Black Trees: Red-Black trees are another popular type of self-balancing BST.

    They assign colors (red or black) to each node and apply specific rules to maintain balance during insertions and deletions.

  • Splay Trees: Splay trees also ensure balance but take a different approach compared to AVL trees and Red-Black trees. They use a technique called “splaying” to bring frequently accessed nodes closer to the root, reducing future access time.

Benefits of Balanced Binary Search Trees

Using balanced binary search trees offers several benefits:

  • Efficient Operations: Since the height of a balanced BST is logarithmic, search, insert, and delete operations have a time complexity of O(log n), where n is the number of elements in the tree.
  • Automatic Balance: Balanced BSTs ensure that the tree remains balanced automatically, eliminating the need for manual rebalancing.
  • Flexible Implementation: Balanced BSTs can be implemented using various programming languages and can be customized based on specific requirements.


A balanced binary search tree provides an efficient way to organize and access elements in a hierarchical manner. By maintaining balance, these trees offer fast operations and reduce time complexity.

Popular types like AVL trees, Red-Black trees, and Splay trees ensure automatic balancing while accommodating different needs. Understanding the concept of balanced binary search trees is essential for developing efficient algorithms and data structures in computer science.

If you want to learn more about data structures or algorithms, consider exploring other tutorials available on our website!

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