Relational Model:

The Relational Model represents how data is stored in Relational Databases. The Relational Model uses Collection of tables to represent data and relationship among them.

Features:

• Data is organized in terms of rows & columns in a table.
• The intersection of a row and column must give a simple value.
• Does not maintain Physical Connection.

 Implementation:

• The Relational Model is implemented with the help of two- dimensional array.
• 
• The field which is common in all data files and is used to link all of them as a database is called Key Field.
• For Example: In table, we see that Roll No. is common in both table is called key field as well as foreign key.

Key Characteristics of Relational Model:

1. Tables (Relations): Data is organized into tables, also known as relations. Each table consists of rows (tuples) and columns (attributes). The rows represent individual records, and the columns represent attributes or fields.

2. Columns (Attributes): Each column in a table represents a specific attribute or characteristic of the data. Columns have names, data types, and constraints that define the kind of data they can store.

3. Rows (Tuples): Rows in a table represent individual records or instances of data. Each row contains a set of values, one for each attribute/column in the table.

4. Primary Key: Each table has a primary key, which is a unique identifier for each row in the table. The primary key ensures the uniqueness of each record and is used to establish relationships between tables.

5. Foreign Key: Foreign keys are used to establish relationships between tables. A foreign key in one table refers to the primary key in another table, creating a link between the two tables.

6. Data Integrity: The relational model enforces data integrity through constraints such as primary key constraints, foreign key constraints, and data type constraints. This ensures the accuracy and consistency of the data.

7. Normalization: Normalization is a process used to organize data in a way that reduces redundancy and dependency. It involves breaking down tables into smaller, more manageable pieces to minimize data duplication.

8. Structured Query Language (SQL): SQL is the standard language for interacting with relational databases. It provides a set of commands for creating, querying, updating, and deleting data in a relational database.

Advantages of Relational Model:

1. Data Integrity: The relational model enforces data integrity through constraints such as primary keys, foreign keys, and unique constraints. This ensures that data is accurate and consistent.

2. Flexibility: It allows for flexible querying using the Structured Query Language (SQL). Users can easily retrieve and manipulate data without having to know the underlying physical storage details.

3. Normalization: The relational model supports normalization techniques, which help reduce data redundancy and improve data integrity. This is achieved by organizing data into well-structured tables.

4. Scalability: Relational databases can handle large amounts of data and scale well as the volume of data increases. This makes them suitable for a wide range of applications from small-scale to enterprise-level systems.

5. Complex Queries: The relational model supports complex queries involving multiple tables through the use of JOIN operations. This allows users to retrieve information from multiple tables in a single query.

6. Security: Relational databases offer features such as access control and user authentication, enhancing data security by restricting unauthorized access to sensitive information.

7. Standardization: The relational model is well-defined and has become a standard in the industry. This standardization promotes interoperability and allows for the development of various tools and applications that work with relational databases.

Disadvantages of Relational Model:

1. Performance: In certain scenarios, the relational model may not perform as well as other data models, especially when dealing with complex queries or large datasets. Optimizing performance may require experienced database administrators.

2. Scalability Challenges: While relational databases can scale, there may be challenges in scaling horizontally across multiple servers, especially in distributed environments. NoSQL databases may offer better scalability in some cases.

3. Fixed Schema: The relational model relies on a fixed schema, meaning that changes to the structure of the database (adding or removing columns) can be challenging and may require downtime.

4. Complexity for Simple Data: For simple and straightforward data storage and retrieval needs, a relational database may introduce unnecessary complexity. In such cases, a NoSQL database might be a more suitable alternative.