Trees in Data Structure: A Hierarchical Approach

 

 Trees in Data Structure: A Hierarchical Approach 

In data structures, a Tree is a hierarchical model used to organize and store data efficiently. Unlike linear structures like arrays and linked lists, trees allow for quick searching, insertion, and deletion operations.

📌 Key Components of a Tree:

1️⃣ Root Node – The topmost node of the tree.
2️⃣ Parent & Child Nodes – Nodes connected by edges, where the parent points to its child nodes.
3️⃣ Leaves (Leaf Nodes) – Nodes with no children.
4️⃣ Subtrees – Smaller trees within the main tree.

🏗 Common Types of Trees:

✅ Binary Tree – Each node has at most two children (left & right).
✅ Binary Search Tree (BST) – A sorted binary tree, where the left child is smaller, and the right child is larger than the parent.
✅ AVL Tree – A self-balancing BST to maintain efficiency.
✅ B-Trees & B+ Trees – Used in databases and file systems.
✅ Trie (Prefix Tree) – Used for searching words efficiently in dictionaries.

📌 Why Use Trees?

🔹 Fast search operations (O(log n) in BSTs).
🔹 Hierarchical data representation (e.g., file systems, DOM structure).
🔹 Efficient storage in databases and memory management.