🚀 Day 3: Types of Databases – Which One Do You Need?

Hey everyone! 👋 Welcome to Day 3 of the SQL tutorial series.

• On Day 1, we learned what SQL is.

• On Day 2, we discussed the difference between a Database and a DBMS.

Today, let’s explore the different types of databases you’ll encounter as you work with data.

Understanding these types will help you know why SQL is used in some databases but not others—and where it shines best!

💾 What is a Database (Quick Recap)?

A database is an organized collection of data, stored electronically so you can easily access, manage, and update it.

But here’s the catch:

• Not all databases are the same!

• Different types are designed for different use cases.

Let’s explore them.

1. Relational Databases (SQL Databases)

This is the type of database you’ll use with SQL.

• Data is stored in tables (rows and columns).

• Tables are related to each other through keys (primary key, foreign key).

• You query data using Structured Query Language (SQL).

Popular relational databases:

• MySQL

• PostgreSQL

• Oracle Database

• SQL Server

• SQLite

Example use cases: E-commerce platforms, Banking systems, HR databases, Inventory management etc.

2. NoSQL Databases (Non-Relational Databases)

• Not every data fits neatly into tables! That’s where NoSQL comes in.

• Designed for flexible data structures like JSON, key-value pairs, graphs, or documents.

• Great for unstructured or semi-structured data.

Types of NoSQL databases:

• Document-based: MongoDB, CouchDB

• Key-Value stores: Redis, DynamoDB

• Column-family: Cassandra, HBase

• Graph databases: Neo4j

Example use cases: Social media networks, Real-time analytics, Recommendation engines, Content management systems

3. Hierarchical Databases

• Data is organized like a tree structure (parent-child relationships).

• Each child record has only one parent.

Mostly used in the early days of databases (like IBM’s IMS), but still in niche legacy systems.

Example use cases: Organization charts, File systems

👉 Rare in modern applications, but foundational for understanding database evolution.

4. Network Databases

• Similar to hierarchical but allows multiple relationships (many-to-many).

• Think of it as a flexible web of connections instead of a strict tree.

• Mostly used in older systems or highly specialized applications.

5. Cloud Databases

• Databases hosted on cloud platforms instead of on-premises servers.

• Can be relational or NoSQL, but managed by a cloud provider.

Examples:

• Amazon RDS (relational)

• Google Cloud Firestore (NoSQL)

• Azure SQL Database

Benefits:

• Scalability

• No physical hardware maintenance

• Built-in backups and replication

👉 Most modern companies now use some form of cloud database.

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🎯Key Differences (Quick Chart)

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📝Why We Focus on Relational Databases in SQL

• Since SQL was specifically designed for relational databases, it’s the foundation for learning structured data querying.

• SQL helps you access and manipulate data when it’s organized in tables.

• Even modern data tools (like BI dashboards) rely on relational databases for reporting.

Once you master SQL, it becomes easier to explore other types of databases too!

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Thanks for following along! Stay tuned for Day 4 🚀