SQL Database Engine - Table Design

Designing Effective Tables in SQL

Proper table design is fundamental to creating efficient, scalable, and maintainable relational databases. This document explores key principles and best practices for designing SQL tables.

Core Concepts

Entities: A table typically represents a real-world entity (e.g., Customers, Products, Orders).
Attributes: Columns in a table represent the attributes or properties of an entity (e.g., CustomerName, ProductPrice, OrderDate).
Primary Key: A column or set of columns that uniquely identifies each row in a table. It enforces entity integrity.
Foreign Key: A column or set of columns in one table that refers to the primary key in another table, establishing relationships and enforcing referential integrity.

Normalization

Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. The most common normal forms are:

Tip: Aim for at least Third Normal Form (3NF) for most transactional databases.

First Normal Form (1NF): Each column contains atomic (indivisible) values, and there are no repeating groups of columns.
Second Normal Form (2NF): Must be in 1NF, and all non-key attributes must be fully functionally dependent on the primary key. (Applies to tables with composite primary keys).
Third Normal Form (3NF): Must be in 2NF, and non-key attributes must not be transitively dependent on the primary key.

Choosing Data Types

Selecting the correct data type for each column is crucial for storage efficiency, data accuracy, and performance. Consider the nature of the data:

Numeric Types: INT, DECIMAL, FLOAT. Choose based on precision and range requirements.
String Types: VARCHAR, NVARCHAR, CHAR. Use VARCHAR for variable-length strings.
Date and Time Types: DATE, TIME, DATETIME, TIMESTAMP.
Binary Types: VARBINARY, BLOB, IMAGE (use sparingly).
Boolean Types: Often represented by BIT or TINYINT (0 for false, 1 for true).

Constraints

Constraints are rules enforced on data columns to ensure accuracy and consistency.

NOT NULL: Ensures a column cannot have a NULL value.
UNIQUE: Ensures all values in a column are distinct.
PRIMARY KEY: Combines NOT NULL and UNIQUE, uniquely identifying rows.
FOREIGN KEY: Enforces referential integrity by linking to a primary key in another table.
CHECK: Limits the range of values that can be placed in a column.

Example: Customer Table Design

Here's an example of a well-designed customer table:

Column Name	Data Type	Constraints	Description
CustomerID	INT	PRIMARY KEY, IDENTITY(1,1)	Unique identifier for the customer.
FirstName	VARCHAR(100)	NOT NULL	Customer's first name.
LastName	VARCHAR(100)	NOT NULL	Customer's last name.
Email	VARCHAR(255)	UNIQUE, NOT NULL	Customer's email address.
PhoneNumber	VARCHAR(20)	NULL	Customer's phone number.
RegistrationDate	DATETIME	NOT NULL, DEFAULT GETDATE()	Date and time the customer registered.

SQL DDL for the example table:


CREATE TABLE Customers (
    CustomerID INT PRIMARY KEY IDENTITY(1,1),
    FirstName VARCHAR(100) NOT NULL,
    LastName VARCHAR(100) NOT NULL,
    Email VARCHAR(255) UNIQUE NOT NULL,
    PhoneNumber VARCHAR(20) NULL,
    RegistrationDate DATETIME NOT NULL DEFAULT GETDATE()
);

Performance Considerations

Indexing: Properly index columns used in WHERE clauses, JOIN conditions, and ORDER BY clauses.
Denormalization: In some cases, selective denormalization can improve read performance, but it comes at the cost of increased redundancy and potential data inconsistency.
Data Archiving: Regularly archive or move old, infrequently accessed data to separate tables or databases.