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Relational databases are a type of database management system (DBMS) that organizes and stores data in a tabular format, with tables consisting of rows (records) and columns (attributes). They are based on the relational model, which was first introduced by Edgar F. Codd in the 1970s. Relational databases have become the most widely used database model due to their simplicity, flexibility, and scalability.

1. Tabular Structure: Relational databases store data in tables, where each table represents a specific entity or concept, and rows represent individual records or instances of that entity. Columns represent attributes or properties of the entity.
2. Relationships: Relational databases use relationships to establish connections between different tables. These relationships define how data in one table is related to data in another table, allowing for efficient data retrieval and querying.
3. Primary Keys and Foreign Keys: Relational databases use primary keys to uniquely identify each record in a table. Foreign keys are used to establish relationships between tables by referencing the primary key of another table.
4. Data Integrity: Relational databases enforce data integrity through various constraints, such as primary key constraints, unique constraints, and referential integrity constraints. These constraints ensure that data is accurate, consistent, and reliable.

Relational databases differ from other database models, such as hierarchical databases, network databases, and object-oriented databases, in several ways.

1. Data Organization: Relational databases organize data in a tabular format, while other models may use different structures like trees or graphs.
2. Data Independence: Relational databases provide a higher level of data independence by separating the logical data representation from the physical storage details. Other models may tightly couple data representation and storage mechanisms.
3. Querying Language: Relational databases use Structured Query Language (SQL) as a standard language for querying and manipulating data. Other models may have their own query languages specific to their data structures and operations.

1. Data Integrity and Consistency: Relational databases enforce data integrity through constraints, ensuring that data is accurate and consistent. This helps maintain data quality and reliability.
2. Flexible Data Manipulation: Relational databases provide a rich set of SQL operations for data manipulation, allowing developers to perform complex queries, joins, aggregations, and sorting operations efficiently.
3. Scalability: Relational databases are highly scalable, allowing for the addition of more data and users without sacrificing performance. They can handle large volumes of data and support concurrent access by multiple users.
4. Data Security: Relational databases offer robust security features, including access controls, user authentication, and encryption mechanisms. This helps protect sensitive data and comply with data privacy regulations.
5. Standardization and Interoperability: Relational databases follow standardized models and query languages, making it easier to share and exchange data between different systems. They promote interoperability and facilitate integration with other applications.

In conclusion, relational databases provide a structured and efficient approach to data management. They offer advantages such as data integrity, flexibility, scalability, and data security, making them a popular choice for application development in various industries. Understanding the principles and characteristics of relational databases is essential for developers and database administrators working with data-driven applications.