Database Systems Chapter 2

Data Models

• Definition: A data model comprises concepts to describe a database's structure, operations, and constraints.
• Structure and Constraints: Constructs define the database's schema, including elements, data types, and relationships. Constraints enforce valid data restrictions.
• Operations: Includes standard operations (insert, delete, update) and user-defined operations (e.g., compute_student_gpa).

Categories of Data Models

• Conceptual Data Models: High-level models reflecting users' perception of data; often entity-based or object-based.
• Physical Data Models: Low-level models that detail data storage mechanisms within the computer.
• Implementation Data Models: Intermediate models applied in commercial DBMS (e.g., relational data models use record structures).
• Self-Describing Data Models: Integrate data description with actual data values; examples are XML and key-value stores.

Schemas versus Instances

• Database Schema: A comprehensive description that outlines structure, data types, and constraints.
• Schema Diagram: Visual representation of schema components such as STUDENT or COURSE.
• Database State: Actual data present in the database at a specific time, also known as database instance.

Database State Insights

• Initial Database State: The data present when first loaded into the system.
• Valid State: A state adhering to the database structure and constraints.
• Distinction: Schemas generally change infrequently while the database state is dynamic—schemas (intension) define structure; state (extension) refers to content.

Three-Schema Architecture

• Designed to enable program-data independence and support multiple data views.
• Levels of Schema:
  • Internal Schema: Details physical storage structures and access paths (e.g., indexes).
  • Conceptual Schema: Provides a unified structure and constraints at the conceptual level for users.