Big Data Chapter 6 – NoSQL Databases | MongoDB and Cassandra Explained

NoSQL Databases in Big Data (MongoDB and Cassandra)

Traditional relational databases struggle with scalability, flexibility, and
performance when handling massive volumes of unstructured and semi-structured data.
NoSQL databases were designed to overcome these limitations.

In Big Data systems, NoSQL databases provide high availability, horizontal scalability,
and fast read-write performance. This chapter introduces NoSQL concepts with a focus
on MongoDB and Cassandra.

⭐ What is NoSQL?

NoSQL (Not Only SQL) databases are non-relational databases designed to store and
process large-scale data efficiently. They support flexible schemas and distributed
architectures.

📌 Why NoSQL Databases are Needed

• Handles massive data volumes
• Supports unstructured and semi-structured data
• Horizontal scalability
• High availability and fault tolerance
• Low-latency read and write operations

📌 Types of NoSQL Databases

• Key-Value Stores: Redis, DynamoDB
• Document Databases: MongoDB
• Column-Family Stores: Cassandra, HBase
• Graph Databases: Neo4j

⭐ MongoDB (Document-Based NoSQL Database)

MongoDB is a document-oriented NoSQL database that stores data in JSON-like
documents called BSON. It is widely used for applications that require flexibility
and rapid development.

📌 Features of MongoDB

• Schema-less document structure
• High performance and scalability
• Easy integration with applications
• Rich querying capabilities

📌 MongoDB Example

// Insert document
db.users.insertOne({
  name: "John",
  age: 30,
  skills: ["Python", "Big Data"]
})

// Find documents
db.users.find({ age: { $gt: 25 } })

📌 MongoDB Use Cases

• Content management systems
• Real-time analytics
• Mobile and web applications

⭐ Apache Cassandra (Column-Family NoSQL Database)

Apache Cassandra is a highly scalable and distributed NoSQL database designed
for handling large amounts of data across multiple nodes with no single point
of failure.

📌 Features of Cassandra

• Peer-to-peer architecture
• Linear scalability
• High availability
• Optimized for write-heavy workloads

📌 Cassandra Data Model

• Keyspace
• Tables
• Rows and columns
• Partition keys and clustering keys

📌 Cassandra Example

CREATE TABLE users (
  user_id UUID PRIMARY KEY,
  name text,
  age int
);

INSERT INTO users (user_id, name, age)
VALUES (uuid(), 'Alice', 28);

📌 Cassandra Use Cases

• Time-series data storage
• IoT applications
• Messaging platforms
• High-volume transactional systems

📌 MongoDB vs Cassandra

• MongoDB: Flexible schema, rich queries
• Cassandra: High write throughput, massive scalability

📌 Real-Life Applications

• Netflix streaming data
• Social media platforms
• Online gaming systems
• E-commerce personalization

📌 Project Title

Scalable Big Data Storage Using MongoDB and Cassandra

📌 Project Description

In this project, you will design a Big Data storage solution using MongoDB
for flexible document storage and Cassandra for high-speed, distributed
data access. This project demonstrates how NoSQL databases are used in
modern Big Data architectures.

📌 Summary

NoSQL databases play a critical role in Big Data systems by enabling scalable,
flexible, and high-performance data storage. MongoDB and Cassandra address
different Big Data needs and are widely adopted in enterprise applications.
This chapter completes your Big Data Technologies course.