RDBMS Concepts, Terminology, Models

A Relational Database Management System (RDBMS) is a type of database management system that is based on the principles of the relational model. RDBMS is widely used in various applications and industries to store, manage, and retrieve structured data efficiently. Understanding the key concepts of RDBMS is essential for designing, implementing, and interacting with relational databases effectively.


Tables are the central building blocks of an RDBMS. They represent the structure to store data in a structured manner. Each table consists of rows (records) and columns (fields). Each row represents a single record or entity, while each column represents a specific attribute or property of that entity.

Rows (Records):

A row, also known as a record, is a single data entry in a table. Each row in a table represents a unique instance of the entity being stored in the database. For example, in a “Customers” table, each row may represent a specific customer, with columns containing their attributes like name, address, and contact information.

Columns (Fields):

Columns, also called fields, represent the attributes or properties of the entities being stored in the table. Each column holds a specific type of data, such as text, numbers, dates, or binary data. In the “Customers” table example, columns could include “CustomerID,” “Name,” “Address,” “Email,” and “Phone.”

Primary Key:

The primary key is a unique identifier for each row in a table. It ensures that each record has a distinct identity and serves as the reference point for linking data across different tables. The primary key must have unique and non-null values, making it a crucial concept for data integrity and efficient data retrieval.

Foreign Key:

A foreign key is a column or set of columns in one table that refers to the primary key in another table. It establishes a relationship between two tables, allowing the RDBMS to maintain referential integrity. Foreign keys are used to create associations between related data in different tables, enabling data consistency and integrity.


Normalization is the process of organizing data in a database to minimize redundancy and improve data integrity. It involves breaking down a large table into smaller, well-structured entities to eliminate data duplication. Normalization helps reduce data anomalies and makes data manipulation more efficient.


Indexes are data structures that improve the performance of database queries by facilitating quick data retrieval. They are created on specific columns of a table and act like a table of contents, enabling the database engine to locate relevant data more efficiently.

SQL (Structured Query Language):

SQL is the standard language used to interact with RDBMS. It allows users to perform various operations, such as inserting, updating, deleting, and querying data in the database. SQL provides a standardized way to communicate with different RDBMSs, making it a powerful and essential tool for database management.

RDBMS models

Relational Database Management Systems (RDBMS) support various data models that define how data is organized, stored, and accessed in the database. The most commonly used data model in RDBMS is the Relational Model, but there are also other specialized data models. Below are the main RDBMS models:

Relational Model:

The Relational Model is the foundation of RDBMS and represents data in the form of tables with rows and columns. Each table represents an entity, and each row in the table represents an instance of that entity, while each column represents an attribute or property of the entity. The relationships between entities are established using primary keys and foreign keys, enabling the management of complex data structures.

Entity-Relationship Model (ER Model):

The ER Model is a high-level data model used to visualize and represent the relationships between entities in a database. It uses entities to represent real-world objects and relationships between these entities to depict how they are related. Entities are represented by rectangles, and relationships are shown using lines connecting the entities.

Object-Relational Model (OR Model):

The Object-Relational Model extends the Relational Model by incorporating object-oriented programming concepts. It allows the storage of complex data types such as arrays, user-defined data types, and methods within the database, blurring the line between traditional relational databases and object-oriented databases.

Hierarchical Model:

The Hierarchical Model represents data in a tree-like structure, where each record has a parent-child relationship with other records. It organizes data in a top-down hierarchical manner, suitable for representing parent-child relationships, but it lacks the flexibility of more modern models like the relational model.

Network Model:

The Network Model is an improvement over the Hierarchical Model, allowing records to have multiple parent-child relationships. It represents data in a graph-like structure, enabling more complex data relationships, but it can be cumbersome to use and maintain compared to the Relational Model.

Object-Oriented Model:

The Object-Oriented Model represents data in the form of objects, similar to object-oriented programming languages. Each object encapsulates both data and methods that operate on the data, allowing for more natural representation of real-world entities.

Dimensional Model (Star Schema and Snowflake Schema):

The Dimensional Model is specifically designed for data warehousing and business intelligence applications. It organizes data into facts and dimensions, enabling fast querying and analysis of large datasets. Star Schema and Snowflake Schema are two common dimensional modeling techniques.

While the Relational Model is the most widely used data model in RDBMS due to its simplicity and flexibility, the other models have their specific use cases and advantages in certain scenarios, such as specialized applications or data warehousing environments.

Leave a Reply

error: Content is protected !!