In this post, we will learn the difference between Heap and Binary Search Tree (BST) in Java. This is a frequently asked question in Java interviews for beginners. Let's dive into it.

Feature | Heap | Binary Search Tree (BST) |
---|---|---|

Structure | Heap is a specialized tree-based data structure where the key of each node is either greater than or equal to (max heap) or less than or equal to (min-heap) the keys of its children. | BST is a binary tree where the left child of a node has a key less than the node's key, and the right child has a key greater than the node's key. |

Balancedness | Heaps are usually not balanced; they are binary trees with some specific ordering properties. | BSTs can be balanced or unbalanced, depending on the order of insertions and deletions. Balanced BSTs (e.g., AVL trees, Red-Black trees) maintain height balance for efficient operations. |

Main Operations | Heap supports efficient insertion, deletion (extract-max or extract-min), and finding the maximum or minimum element in O(log n) time complexity. | BST supports efficient search, insertion, and deletion operations in O(log n) time complexity for balanced trees. For unbalanced BSTs, the time complexity may degrade to O(n) in the worst case. |

Use Cases | Heaps are commonly used in priority queues and heap-based sorting algorithms like Heap Sort. | BSTs are used for fast searching and dynamic data sets where elements are inserted and removed frequently, such as in database indexing and symbol tables. |

Implementation | Heaps are usually implemented as arrays with heapification algorithms to maintain the heap property. | BSTs are implemented using linked data structures (nodes with left and right pointers) or array representation (e.g., array-based BSTs). |

In-order Traversal | Heap does not guarantee in-order traversal; it only satisfies the heap property. | BST's in-order traversal visits the nodes in ascending order (sorted order) if the tree is balanced. |

Time Complexity for Searching | Heap has O(n) time complexity for searching an element as there is no specific order among the elements in each level. | Balanced BST has O(log n) time complexity for searching, as it halves the search space in each step. |

Heap Property | The heap property ensures that the root node has the highest (max heap) or lowest (min-heap) key among all the nodes in the heap. | BST property ensures that the left subtree of a node contains keys less than the node's key, and the right subtree contains keys greater than the node's key. |

Example |