Questions
16 of 26
1What is a Tree? Define Node, Root, Leaf, Edge, Height, Depth.
2What is a Binary Tree?
3What is a Binary Search Tree (BST)? What are its properties?
4What is the difference between a Binary Tree and a Binary Search Tree?
5Explain Tree Traversals: Inorder, Preorder, Postorder, Level Order.
6How do you implement Inorder traversal iteratively? (Without recursion)
7How do you find the Lowest Common Ancestor (LCA) of two nodes in a BST?
8How do you validate if a given Tree is a valid BST?
9What is a Balanced Tree? Why do we need balance?
10What is a Complete Binary Tree? A Full Binary Tree? A Perfect Binary Tree?
11What is a Heap? (Min-Heap and Max-Heap)
12How is a Heap implemented using an Array? (Parent/Child index math)
13What is the time complexity of insertion and deletion in a Heap? Why?
14What is Heapify? Explain the process.
15What is a Trie (Prefix Tree)? When is it used?
16How does a Trie compare to a Hash Table for string storage?
17What is an AVL Tree? What is a Red-Black Tree? What is the difference?
18Why do databases prefer B-Trees/B+ Trees over Binary Search Trees?
19How do you serialize and deserialize a Binary Tree?
20What is a Segment Tree? What problems does it solve?
21What is a Fenwick Tree (Binary Indexed Tree)?
22What is the difference between a B-Tree and a B+ Tree? Why are B+ Trees better for disk access?
23Explain the concept of Tree Rotation.
24What is a Splay Tree? When would you use it?
25How do you find the diameter of a Binary Tree?
26How do you check if a tree is symmetric (Mirror image)?
Data-StructuresData-Structures
Basics
Complexity Analysis
Arrays and Strings
Linked Lists
Stacks and Queues
Hash Tables
Trees
Graphs
16 / 26

How does a Trie compare to a Hash Table for string storage?

Difficulty: 4/10

Trie vs Hash Table

A hash table is excellent for exact key lookup, typically providing O(1) average lookup, but it does not naturally support ordered or prefix-based queries. A Trie supports exact lookup as well as prefix operations in O(L), where L is the string length, but usually consumes more memory because of its node and child references.

javascript
  1. 1

    Hash table: better for exact membership and key-value lookup.

  2. 2

    Trie: better for prefix search and autocomplete.

  3. 3

    Hash table usually has lower structural memory overhead.

  4. 4

    Trie can share common prefixes between strings.

  5. 5

    Choice depends on workload, memory constraints, and query patterns.

Follow-up Questions

  • How can a Trie be compressed?
  • When would a hash table be a better choice?
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