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Difference between Min Heap and Max Heap

Last Updated : 2 Oct, 2025

A Heap is a special Tree-based data structure in which the tree is a complete binary tree. Since a heap is a complete binary tree, a heap with N nodes has log N height. It is useful to remove the highest or lowest priority element. It is typically represented as an array. There are two types of Heaps in the data structure.

In a Min-Heap the key present at every node node node must be less than all of its children. In a Min-Heap the minimum key element present at the root. Below is the Binary Tree that satisfies all the property of Min Heap.

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In a Max-Heap the key present at every node node must be greater than at all of its children. In a Max-Heap the maximum key element present at the root. Below is the Binary Tree that satisfies all the property of Max Heap.

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Min HeapMax Heap
1.In a Min-Heap the key present at the root node must be less than all of its descendants and same thing must be true for all subtrees,In a Max-Heap the key present at the root node must be more than all of its descendants and same thing must be true for all subtrees,
2.In a Min-Heap the minimum key element present at the root.In a Max-Heap the maximum key element present at the root.
3.A Min-Heap uses the ascending priority.A Max-Heap uses the descending priority.
4.In the construction of a Min-Heap, the smallest element has priority.In the construction of a Max-Heap, the largest element has priority.
5.In a Min-Heap, the smallest element is the first to be popped from the heap.In a Max-Heap, the largest element is the first to be popped from the heap.

:

  1. Heap Sort: Heap Sort is one of the best sorting algorithms that use Binary Heap to sort an array in O(N*log N) time.
  2. Priority Queue: A priority queue can be implemented by using a heap because it supports insert(), delete(), extractMax(), decreaseKey() operations in O(log N) time.
  3. Graph Algorithms: The heaps are especially used in Graph Algorithms like Dijkstra’s Shortest Path and Prim’s Minimum Spanning Tree.

:

  • Get Maximum or Minimum Element: O(1)
  • Insert Element into Max-Heap or Min-Heap: O(log N)
  • Remove Maximum (in max heap) or Minimum (in min heap) : O(log N)
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