Tables: The Building Blocks of Relational Databases

• Definition and Purpose: Tables represent entities or concepts in your data model. Each table stores information about a specific type of object (customers, products, transactions, etc.).
• Naming Conventions: Best practices for naming tables (singular vs. plural, prefixing, etc.)
• Table Properties: Understanding table characteristics such as storage engines, collation, and compression options
• Temporary vs. Permanent Tables: When and how to use each type
• System Tables vs. User Tables: Differentiating between database-managed tables and user-created tables
• Partitioned Tables: Introduction to table partitioning for performance optimization

Columns and Data Types

• Column Definition: Understanding attributes that define columns (name, data type, constraints)
• Data Type Selection: Choosing appropriate data types for different kinds of information
  • Numeric types (INT, DECIMAL, FLOAT, etc.)
  • Character types (CHAR, VARCHAR, TEXT)
  • Date/time types (DATE, DATETIME, TIMESTAMP)
  • Binary types (BLOB, BINARY)
  • Special types (JSON, XML, spatial data types)
• Column Constraints: NOT NULL, DEFAULT, CHECK, UNIQUE
• Computed/Generated Columns: Creating columns based on expressions
• Column Storage and Performance Implications: How column choices affect storage and query speed

Rows: The Actual Data

• Row Structure: How data is physically stored within rows
• Row Size Limitations: Understanding maximum row sizes in different database systems
• Row Operations: INSERT, UPDATE, DELETE conceptual overview
• Row Versioning: How databases track changes for concurrency control
• Row Locking: Introduction to how databases manage concurrent access to rows
• Statistics and Cardinality: How the number of rows affects query performance

Keys: Ensuring Data Integrity and Relationships

Primary Keys

• Definition and Importance: Unique identifier for each record in a table
• Selection Criteria: Guidelines for choosing effective primary keys
• Natural vs. Surrogate Keys: Using existing data vs. system-generated identifiers
• Composite Primary Keys: When and how to use multiple columns as a primary key
• Implementation Options: AUTO_INCREMENT, IDENTITY, Sequences, UUIDs
• Performance Considerations: Indexing, clustering, and storage implications

Foreign Keys

• Purpose and Function: Establishing and enforcing relationships between tables
• Referential Integrity: Ensuring data consistency across related tables
• Constraint Actions: CASCADE, SET NULL, SET DEFAULT, RESTRICT, NO ACTION
• One-to-Many, Many-to-Many, and One-to-One Relationships: Implementation patterns
• Self-Referencing Foreign Keys: Handling hierarchical data
• Performance Implications: How foreign keys affect INSERT, UPDATE, and DELETE operations
• Deferrable Constraints: Delaying constraint checks until transaction commit

Practical Applications and Best Practices

• Normalization and Denormalization: Balancing data integrity and performance
• Entity-Relationship Modeling: Designing tables and relationships
• Indexing Strategies: Optimizing key columns for query performance
• Data Migration Considerations: Moving data while maintaining relationships
• Versioning and Temporal Data: Managing historical data with effective key strategies
• Scale Considerations: How key choices affect database scalability