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Introduction to Data Structures

What is a Data Structure?​

A data structure is a way of organizing, storing, and managing data so it can be accessed and modified efficiently.
It shapes how data lives in memory and how algorithms interact with it.

In simple terms:

Data structures decide how data is arranged, while algorithms decide what to do with it.

Why Data Structures Matter​

Choosing the right data structure can dramatically change:

  • Performance of an application
  • Memory usage
  • Scalability
  • Code simplicity and maintainability

The same problem solved with different data structures can feel like:

  • walking vs taking an express train 🚆

Data Structures vs Algorithms​

  • Data Structures: How data is stored
  • Algorithms: How data is processed

They work as a pair. A powerful algorithm on a poor data structure is inefficient, and a great data structure without the right algorithm is underused.

Classification of Data Structures​

Primitive Data Structures​

Basic data types provided by programming languages:

  • Integer
  • Floating-point
  • Character
  • Boolean
  • Reference
  • Enumerated types

Non-Primitive Data Structures​

Formed using primitive types:

  • Arrays
  • Strings
  • Records / Structs
  • Unions

Abstract Data Types (ADT)​

Define behavior without implementation details:

  • List
  • Stack
  • Queue
  • Set
  • Map
  • Graph

Linear Data Structures​

Data elements arranged sequentially:

  • Arrays
  • Lists
  • Stacks
  • Queues

Non-Linear Data Structures​

Data elements arranged hierarchically or graph-like:

  • Trees
  • Heaps
  • Graphs
  • Hash-based structures

Key Operations on Data Structures​

Most data structures support a combination of:

  • Insertion
  • Deletion
  • Traversal
  • Searching
  • Sorting
  • Updating

Time and Space Complexity​

Efficiency is measured using:

  • Time Complexity: How fast an operation runs
  • Space Complexity: How much memory it uses

Big-O notation is commonly used to describe both.

Real-World Applications​

Data structures power:

  • Operating systems
  • Databases
  • Compilers
  • Search engines
  • Social networks
  • Game engines

Every modern system is built on carefully chosen data structures.

How to Use This Documentation​

This documentation is organized to:

  • Start with core concepts
  • Group related structures together
  • Use comparison tables for quick understanding
  • Focus on practical use cases

Each section builds intuition first, details second.

Final Thought​

Learning data structures is not about memorizing definitions.
It’s about understanding trade-offs, patterns, and how data flows through systems.

Once you see the structure, the code follows naturally 🌱