Database

Database Design Guide

Overview

Database design is the process of creating a detailed data model of a database that defines the logical structure, relationships, constraints, and organization of data. Good database design ensures data integrity, reduces redundancy, optimizes performance, and supports business requirements.

Database Design Process

1. Requirements Analysis

Gather Business Requirements

  • Identify what data needs to be stored
  • Understand business rules and constraints
  • Determine user roles and access patterns
  • Analyze data volume and growth expectations
  • Define performance requirements

Questions to Ask:

  • What information does the business need to track?
  • How will the data be used?
  • Who will access the data?
  • What are the reporting requirements?
  • What are the security and compliance needs?

2. Conceptual Design

Entity-Relationship (ER) Modeling

  • Identify entities (things/objects to store data about)
  • Define attributes (properties of entities)
  • Establish relationships between entities
  • Determine cardinality (one-to-one, one-to-many, many-to-many)

Key Components:

  • Entities: Customer, Product, Order, Employee
  • Attributes: CustomerID, Name, Email, Phone
  • Relationships: Customer places Order, Order contains Product
  • Constraints: Business rules and data validation

3. Logical Design

Convert ER Model to Relational Schema

  • Transform entities into tables
  • Convert attributes to columns
  • Implement relationships through foreign keys
  • Apply normalization rules
  • Define primary and foreign keys

Normalization Process:

  • 1NF (First Normal Form): Eliminate repeating groups
  • 2NF (Second Normal Form): Remove partial dependencies
  • 3NF (Third Normal Form): Eliminate transitive dependencies
  • BCNF (Boyce-Codd Normal Form): Stricter version of 3NF

4. Physical Design

Database Implementation Decisions

  • Choose appropriate data types
  • Design indexes for performance
  • Partition large tables if needed
  • Configure storage parameters
  • Plan for backup and recovery

Key Design Principles

1. Data Integrity

Primary Keys

  • Unique identifier for each record
  • Cannot be null
  • Should be stable (not change over time)
  • Consider using surrogate keys (auto-increment IDs)

Foreign Keys

  • Maintain referential integrity
  • Link related tables
  • Prevent orphaned records
  • Define cascade actions (DELETE/UPDATE)

Constraints

  • NOT NULL constraints
  • CHECK constraints for data validation
  • UNIQUE constraints for alternate keys
  • Default values for columns

2. Normalization vs. Denormalization

When to Normalize:

  • Reduce data redundancy
  • Prevent update anomalies
  • Save storage space
  • Maintain data consistency

When to Denormalize:

  • Improve query performance
  • Reduce complex joins
  • Meet specific reporting needs
  • Handle read-heavy workloads

3. Indexing Strategy

Types of Indexes:

  • Clustered Index: Physical ordering of data
  • Non-clustered Index: Logical ordering with pointers
  • Composite Index: Multiple columns
  • Unique Index: Ensures uniqueness
  • Partial Index: Subset of rows

Index Design Guidelines:

  • Index frequently queried columns
  • Index foreign key columns
  • Consider composite indexes for multi-column queries
  • Avoid over-indexing (impacts INSERT/UPDATE performance)
  • Monitor and maintain index statistics

Database Design Patterns

1. Common Table Patterns

Lookup Tables

CREATE TABLE Status (
    StatusID INT PRIMARY KEY,
    StatusName VARCHAR(50) NOT NULL,
    Description TEXT
);

Junction Tables (Many-to-Many)

CREATE TABLE OrderProduct (
    OrderID INT,
    ProductID INT,
    Quantity INT,
    UnitPrice DECIMAL(10,2),
    PRIMARY KEY (OrderID, ProductID),
    FOREIGN KEY (OrderID) REFERENCES Orders(OrderID),
    FOREIGN KEY (ProductID) REFERENCES Products(ProductID)
);

Audit Tables

CREATE TABLE CustomerAudit (
    AuditID INT PRIMARY KEY AUTO_INCREMENT,
    CustomerID INT,
    Action VARCHAR(10), -- INSERT, UPDATE, DELETE
    OldValues JSON,
    NewValues JSON,
    ChangedBy VARCHAR(100),
    ChangedAt TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

2. Hierarchical Data

Self-Referencing Tables

CREATE TABLE Categories (
    CategoryID INT PRIMARY KEY,
    CategoryName VARCHAR(100),
    ParentCategoryID INT,
    FOREIGN KEY (ParentCategoryID) REFERENCES Categories(CategoryID)
);

Nested Set Model (for complex hierarchies)

  • Use Left and Right values to represent tree structure
  • Efficient for read operations
  • Complex for updates

Best Practices

1. Naming Conventions

Tables

  • Use singular nouns: Customer, not Customers
  • Use PascalCase or snake_case consistently
  • Avoid reserved words and special characters

Columns

  • Use descriptive names: CustomerFirstName vs CFN
  • Include data type hints: CreatedDate, IsActive
  • Use consistent naming patterns

Keys and Constraints

  • Primary Key: PK_TableName
  • Foreign Key: FK_TableName_ReferencedTable
  • Index: IX_TableName_ColumnName
  • Check Constraint: CK_TableName_ColumnName

2. Data Types

Choose Appropriate Types

  • Use smallest data type that fits requirements
  • VARCHAR vs CHAR: Use VARCHAR for variable length
  • INT vs BIGINT: Consider future growth
  • DECIMAL for precise numeric values
  • Use appropriate date/time types

Common Data Type Guidelines

  • Email: VARCHAR(254)
  • Phone: VARCHAR(20)
  • Currency: DECIMAL(19,4)
  • Boolean: BOOLEAN or TINYINT(1)
  • Large Text: TEXT or NVARCHAR(MAX)

3. Security Considerations

Access Control

  • Implement role-based security
  • Use principle of least privilege
  • Create database users for applications
  • Avoid using admin accounts for applications

Data Protection

  • Encrypt sensitive data
  • Use secure connection strings
  • Implement field-level encryption for PII
  • Regular security audits

4. Performance Optimization

Query Optimization

  • Write efficient SQL queries
  • Use appropriate JOIN types
  • Limit result sets with WHERE clauses
  • Use LIMIT/TOP for pagination

Database Maintenance

  • Regular index maintenance
  • Update table statistics
  • Monitor query execution plans
  • Archive old data

Documentation and Maintenance

1. Database Documentation

Essential Documentation

  • ER diagrams
  • Table structure with descriptions
  • Business rules and constraints
  • Data dictionary
  • Index strategy
  • Security model

2. Version Control

Schema Versioning

  • Use migration scripts
  • Track schema changes
  • Test migrations on development environment
  • Plan rollback strategies

3. Monitoring and Maintenance

Regular Tasks

  • Monitor performance metrics
  • Check for index fragmentation
  • Review slow query logs
  • Update statistics
  • Plan for capacity growth

Tools and Technologies

1. Design Tools

ER Modeling Tools

  • MySQL Workbench
  • Microsoft Visio
  • Lucidchart
  • Draw.io
  • dbdiagram.io

Database Administration

  • phpMyAdmin (MySQL)
  • SQL Server Management Studio
  • pgAdmin (PostgreSQL)
  • Oracle SQL Developer
  • DBeaver (Multi-platform)

2. Development Approaches

Database-First

  • Design database schema first
  • Generate application models from database
  • Traditional approach for data-centric applications

Code-First

  • Define models in application code
  • Generate database from code models
  • Common in modern ORM frameworks

Model-First

  • Create conceptual model first
  • Generate both database and code
  • Balance between database-first and code-first

Conclusion

Effective database design requires careful planning, understanding of business requirements, and adherence to established principles. The key is to balance normalization with performance, ensure data integrity, and plan for future growth and changes. Regular review and optimization of the database design will help maintain performance and meet evolving business needs.

Remember that database design is an iterative process, and it's common to refine the design as requirements become clearer or business needs change.