Questions
18 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
18 / 26

Why do databases prefer B-Trees/B+ Trees over Binary Search Trees?

Difficulty: 5/10

Database Index Trees

Databases operate primarily on storage systems where disk or SSD I/O is far more expensive than an in-memory pointer operation. B-Trees and B+ Trees have high branching factors, which make the tree shallow and reduce the number of pages that must be read. B+ Trees also place records or record pointers in leaves and link the leaves, making range scans efficient.

javascript
  1. 1

    High fan-out reduces tree height.

  2. 2

    Nodes are designed around storage pages or blocks.

  3. 3

    Fewer levels mean fewer I/O operations.

  4. 4

    B+ Tree leaves support efficient sequential and range scans.

  5. 5

    Database indexes need predictable performance at large scale.

Follow-up Questions

  • Why are database B+ Tree nodes aligned with pages?
  • How does a B+ Tree support range queries efficiently?
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