If you’re learning data structures, you’ve probably heard of Binary Tree and Binary Search Tree (BSTs). While they may look similar, they have key differences in storing and organizing the data.
In this post, let’s break down the difference in a simple and clear way.
What is a Binary Tree?
A Binary Tree is a tree data structure where each node can have at most two children:
- Left child
- Right child
It’s used to represent hierarchical data and doesn’t follow any sorting rule.
Example:
A
/ \
B C
/ \
D E
There’s no order between the values of parent and child nodes.
What is a Binary Search Tree (BST)?
A BST is a type of BT that follows a special rule:
- Left child < Parent
- Right child > Parent
This rule helps keep the tree sorted, which makes searching and inserting data faster.
Example:
50
/ \
30 70
/ \ \
20 40 90
Each node follows: Left < Root < Right
Key Differences:
Feature BT (BST)
Structure Rule No specific rule Left < Root < Right
Data Arrangement Random / unordered Sorted by value
Search Time Slower (O(n)) Faster (O(log n), if balanced)
Use Case General tree problems Fast searching, insertion, deletion
Inorder Traversal Any order Always sorted
Real-world Use Expression trees, parsing Databases, search systems
In Simple Words:
- A Binary Tree is just a way to connect nodes — no rules about values.
- A BST is a smart Binary Tree that keeps data sorted and searchable.
Binary Tree Node:
class Node:
def _init_(self, value):
self.value = value
self.left = None
self.right = None
BST Insertion:
def insert(root, value):
if root is None:
return Node(value)
if value < root.value:
root.left = insert(root.left, value)
else:
root.right = insert(root.right, value)
return root
Interview Tips:
Q: Is every BST a Binary Tree?
A: Yes.
Q: Is every Binary Tree a BST?
A: No.
Final Summary:
BT (BST)
Just a tree structure Sorted tree with rules
No order of values Follows left < root < right rule
Slower operations Faster search and insert
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