Relational Vs. Non-Relational Databases

Relational Database Design and Modeling for Software Engineers

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Relational Databases (RDBMS)

Relational databases organize data into structured tables with rows and columns. Each table represents an entity, and tables can be linked through relationships defined by primary and foreign keys. Relational databases use Structured Query Language (SQL) for defining, querying, and managing data.

Key Features:

Predefined schema
ACID compliance (ensures data reliability)
Strong data integrity and consistency

Examples: MySQL, PostgreSQL, Oracle Database, Microsoft SQL Server.

Non-Relational Databases (NoSQL)

Non-relational databases store data in a flexible format that can handle structured, semi-structured, or unstructured data. They are designed for scalability and performance in handling large volumes of data and can use formats such as documents, key-value pairs, graphs, or wide columns.

Key Features:

Flexible schema
High scalability
Optimized for large-scale data and fast read/write operations

Examples: MongoDB, Cassandra, Redis, Neo4j.

Relational vs. Non-Relational Databases

Feature	Relational Databases (RDBMS)	Non-Relational Databases (NoSQL)
Schema	Fixed, predefined schema	Flexible schema
Data Model	Tables with rows and columns	Various (document, key-value, graph, columnar)
Query Language	SQL	No fixed query language (varies by type)
Scalability	Vertical (adding more power to one server)	Horizontal (adding more servers)
ACID Compliance	Strong ACID compliance	Typically supports BASE properties
Data Integrity	High data integrity with strict relationships	Data integrity varies, often application-managed
Best Use Cases	Financial systems, CRM, ERP	Real-time analytics, content management, IoT

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