Relational Data Model

1. Relation

A relation is a table consisting of rows and columns. For example, STUDENT is a relation containing student records.

2. Schema

A schema defines the structure of a relation — the ordered list of attributes and their types. Example: STUDENT(STUD_ID, NAME, PHONE, STATE, STUD_AGE).

3. Instance

An instance is the set of tuples (rows) present in a relation at a given moment — i.e., the current content of the table.

4. Attribute

An attribute is a column in a relation that describes a property of the entity, e.g., NAME, PHONE for STUDENT.

5. Domain

A domain is the set of permitted values for an attribute. Example: the AGE attribute may allow values between 21 and 32.

6. Tuple

A tuple is a single row in a relation — a single record storing values for all attributes.

7. Null Values

Null represents unknown, missing or undefined data. NULL is distinct from zero or empty string, and most operations involving NULL produce NULL (or use special semantics).

• Data integrity: built-in mechanisms (constraints) ensure accuracy and consistency.
• Reduced redundancy: normalization helps eliminate duplicate data.
• Access control & validation: constraints and privileges validate and restrict data access.
• Security: RDBMSs provide authentication, authorization and auditing.
• Support for many data types: numbers, strings, dates, large objects (images, audio) etc.
• Multi-user access: concurrency control allows many users to work simultaneously.
• Interoperability: data and queries can be shared across platforms and tools.

Note: Modern RDBMS implementations (Oracle, PostgreSQL, MySQL, SQL Server, etc.) are highly optimized for transaction processing and analytics across varied deployments.