The debate between the application of NoSQL and SQL is one of the most difficult choices for companies and app developers. Each type of database has its strengths, and choosing one depends on your app development needs. In this article, you will learn everything you need to know about NoSQL vs SQL databases and when to use each for your application.

1. NoSQL vs. SQL Databases
A comparison of NoSQL and SQL databases. Each database has strengths.
Choosing one depends on your app development needs.
by Intellisource Technologies

2. SQL Databases: Overview
SQL databases use Structured Query Language. Data is structured in tables
with rows and columns. SQL databases are used in finance and enterprise
products.
They are best when data relationships are essential.
Structured Data
Organized in tables.
Relational
Relationships between data are
key.
ACID Compliant
Ensures transaction reliability.

3. Popular SQL Databases
• MySQL: Fast and stable.
• PostgreSQL: High-performance RDBMS.
• Microsoft SQL Server: Strong connectivity.
• Oracle Database: For large-scale apps.
• SQLite: Lightweight, for mobile use.
MySQL PostgreSQL SQL Server

4. Advantages of SQL
Databases
1 Structured Storage
Manages structured data effectively.
2 ACID Compliance
Reliable transaction execution.
3 Robust Querying
Sophisticated data manipulation.
4 Widely Adopted
Extensive community support.

5. NoSQL Databases: Overview
NoSQL databases are non-relational. They are not based on a fixed schema and are
highly scalable. NoSQL suits applications needing speed and easy scalability.
They are ideal for dynamic and real-time systems.
Flexible
No fixed schema.
Scalable
Handles large data.
High Speed
For real-time apps.

6. Popular NoSQL Databases
• MongoDB: Document-based, JSON-like.
• Cassandra: High availability, scale-out.
• Couchbase: Document-oriented, key-value.
• DynamoDB: Managed NoSQL by AWS.
• Redis: Fast, in-memory key-value store.
MongoDB Cassandra Couchbase

7. Advantages of NoSQL Databases
1 Scalability
Manages vast datasets.
2 Flexibility
Supports various data models.
3 High Performance
Real-time analytics.
4 Dynamic Schemas
Adapts to evolving data.

8. When to Choose
SQL
• Structured data.
• Transactional integrity.
• Complex queries.
• Legacy integration.
NoSQL
• Unstructured data.
• High-speed operations.
• Scalability.
• Frequent schema changes.