3.3 Relational Database Management Systems (RDBMS)

Relational Database Management Systems (RDBMS) are the backbone of modern data storage and retrieval. They organize information into tables with predefined relationships, making it easy to manage and query large amounts of data efficiently.

RDBMS use Structured Query Language (SQL) to manipulate data and enforce ACID properties for reliable transactions. Key concepts include tables, relationships, and constraints, which ensure data integrity and provide a solid foundation for complex applications.

Relational Database Concepts

Fundamental Principles

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• Relational database stores and organizes data in tables with predefined relationships
• Relational model developed by Edgar F. Codd represents data as relations or tables
• Structured Query Language (SQL) manages and manipulates relational databases
  • Used for data definition, manipulation, and control
• Normalization organizes data to reduce redundancy and improve integrity
  • Achieved through a series of normal forms
• ACID properties ensure reliable processing of database transactions
  • Atomicity, Consistency, Isolation, Durability

Key Components

• Entities represent distinct objects or concepts in a database
  • Examples: Customer, Product, Order
• Attributes describe properties or characteristics of entities
  • Examples: CustomerName, ProductPrice, OrderDate
• Relationships define associations between entities
  • Typically represented by foreign key constraints
  • Examples: Customer places Order, Order contains Product

Relational Database Structure

Table Components

• Tables (relations) store data in rows (tuples) and columns (attributes)
• Columns represent attributes or fields of an entity
  • Defined by specific data types (integer, varchar, date)
• Rows contain actual data values for each attribute
  • Represent individual instances of the entity
• Schema defines table structure
  • Includes column names, data types, and constraints

Database Objects

• Indexes improve speed of data retrieval operations
  • Create separate data structure for faster searching
  • Examples: B-tree index, Hash index
• Views present data in specific format or with restricted access
  • Virtual tables derived from one or more base tables
  • Example: CustomerOrderView combining Customer and Order tables
• Stored procedures are precompiled SQL statements
  • Improve performance and code reusability
  • Example: CalculateOrderTotal procedure

Relational Database Properties

Key Constraints

• Primary keys uniquely identify each row in a table
  • Ensure data integrity and provide reference for specific records
  • Example: CustomerID in Customer table
• Foreign keys establish relationships between tables
  • Reference primary key of another table
  • Maintain referential integrity
  • Example: CustomerID in Order table referencing Customer table
• Unique constraints ensure column values are unique across all rows
  • Can be applied to single or multiple columns
  • Example: Email column in User table

Data Integrity Constraints

• Check constraints define rules for data validity
  • Enforce conditions before inserting or updating data
  • Example:

    CHECK (Age >= 18)

    for adult-only services
• Not Null constraints specify columns cannot contain empty values
  • Ensure required data presence
  • Example: ProductName column in Product table
• Default constraints provide fallback values for columns
  • Used when no value specified during data insertion
  • Example:

    DEFAULT CURRENT_TIMESTAMP

    for CreatedDate column
• Referential integrity prevents orphaned records or invalid references
  • Maintains consistency between related tables
  • Example: Deleting a customer cascades to related orders

Advantages of RDBMS

Data Management and Organization

• Provides structured and efficient storage for large amounts of data
  • Suitable for complex business applications (banking systems, e-commerce platforms)
• Data independence allows changes to physical storage without affecting logical structure
  • Improves flexibility and scalability
• Concurrent access control enables multiple users to access and modify data simultaneously
  • Maintains data consistency through locking mechanisms

Security and Integrity

• Built-in security features protect sensitive data
  • User authentication and access control
  • Example: Role-based access for different user types
• Data integrity maintained through constraints and ACID properties
  • Ensures accuracy and consistency of stored information
  • Example: Preventing negative values in price columns

Query Capabilities and Standardization

• Supports complex queries and data analysis through SQL
  • Enables sophisticated data retrieval and manipulation
  • Example: Joining multiple tables for comprehensive reports
• Standardization of RDBMS and SQL allows easier integration and portability
  • Facilitates data migration between different database systems
  • Example: Moving data from MySQL to PostgreSQL with minimal changes