SQL Data Types and Constraints

Beginner⏱20-30 minutes📖4 min readLesson 7 of 10

SQL Data Types and Constraints

Deep dive into SQL data types (INT, VARCHAR, TEXT, DATE, DECIMAL) and constraints (NOT NULL, UNIQUE, PRIMARY KEY, FOREIGN KEY, CHECK, DEFAULT)

Choosing the right data type and applying appropriate constraints ensures data integrity, optimizes storage, and prevents application bugs.

SQL Data Types

Numeric Types

Type	Storage	Range / Precision	Use Case
`INTEGER` / `INT`	4 bytes	-2^31 to 2^31-1	Counts, IDs, ages
`SMALLINT`	2 bytes	-32,768 to 32,767	Small ranges, status codes
`BIGINT`	8 bytes	-2^63 to 2^63-1	Large counters, big IDs
`DECIMAL(p,s)`	Variable	Exact precision	Money, scientific measurements
`REAL` / `FLOAT`	4-8 bytes	Approximate	Percentages, averages (not money!)

sql

CREATE TABLE products (
    id INTEGER PRIMARY KEY,
    price DECIMAL(10,2) NOT NULL,  -- 10 digits, 2 after decimal
    rating DECIMAL(3,2),            -- e.g. 4.75
    stock SMALLINT DEFAULT 0
);

⚠️Warning

Never use FLOAT or REAL for monetary values. Floating-point rounding errors (e.g., 0.1 + 0.2 = 0.30000000000000004) will cause accounting discrepancies. Always use DECIMAL.

Character/String Types

Type	Description	Use Case
`CHAR(n)`	Fixed-length, padded with spaces	Codes, zip codes, hashes
`VARCHAR(n)`	Variable-length with max	Names, emails, addresses
`TEXT`	Unlimited length	Articles, descriptions, JSON

sql

CREATE TABLE articles (
    title VARCHAR(200) NOT NULL,
    slug VARCHAR(200) NOT NULL,
    body TEXT,
    excerpt VARCHAR(500)
);

ℹ️Note

VARCHAR(255) is a common default because 255 is the max length that can be encoded with a single byte prefix. Use TEXT when content can exceed a few hundred characters.

Date/Time Types

Type	Format	Example	Precision
`DATE`	YYYY-MM-DD	2024-01-15	Day
`TIME`	HH:MM:SS	14:30:00	Second
`TIMESTAMP`	YYYY-MM-DD HH:MM:SS	2024-01-15 14:30:00	Second (or sub-second)
`DATETIME`	YYYY-MM-DD HH:MM:SS	2024-01-15 14:30:00	No timezone (MySQL)

sql

CREATE TABLE events (
    event_name VARCHAR(200),
    event_date DATE,
    start_time TIME,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

Other Useful Types

Type	Use Case
`BOOLEAN`	True/false flags
`BLOB`	Binary data (images, files)
`JSON`	Structured nested data (PostgreSQL, MySQL)
`UUID`	Universally unique identifiers
`ENUM`	Fixed list of values (MySQL)

Constraints

Constraints enforce rules on the data in your tables.

NOT NULL

Ensures a column cannot contain NULL:

sql

CREATE TABLE users (
    email VARCHAR(255) NOT NULL,
    name VARCHAR(100) NOT NULL
);

sql

-- This will fail
INSERT INTO users (name) VALUES ('Alice');  -- email is NULL, violates NOT NULL

UNIQUE

Ensures all values in a column (or combination of columns) are distinct:

sql

CREATE TABLE users (
    email VARCHAR(255) NOT NULL UNIQUE,
    username VARCHAR(50) NOT NULL UNIQUE
);

sql

-- This will fail
INSERT INTO users (email, username) VALUES ('a@x.com', 'alice');
INSERT INTO users (email, username) VALUES ('b@x.com', 'alice');  -- duplicate username

✅Success

UNIQUE also creates an index, making lookups fast. Use it for natural keys like email, username, or SKU.

PRIMARY KEY

Uniquely identifies each row. Combines NOT NULL + UNIQUE. A table can have only one:

sql

-- Single column PK
CREATE TABLE users (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    email VARCHAR(255) NOT NULL
);

-- Composite PK (multiple columns)
CREATE TABLE order_items (
    order_id INTEGER,
    product_id INTEGER,
    quantity INTEGER,
    PRIMARY KEY (order_id, product_id)
);

FOREIGN KEY

Links rows across tables and maintains referential integrity:

sql

CREATE TABLE orders (
    id INTEGER PRIMARY KEY,
    user_id INTEGER NOT NULL,
    FOREIGN KEY (user_id) REFERENCES users(id)
    ON DELETE CASCADE
    ON UPDATE CASCADE
);

Referential Actions

Action	On Delete	On Update
`CASCADE`	Delete child rows	Update child FK values
`SET NULL`	Set child FK to NULL	Set child FK to NULL
`RESTRICT`	Prevent parent delete	Prevent parent update
`NO ACTION`	Same as RESTRICT (check deferrable)
`SET DEFAULT`	Set to default value	Set to default value

sql

-- If user is deleted, their orders are also deleted
FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE CASCADE

-- If user is deleted, orders keep user_id as NULL
FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE SET NULL

⚠️Warning

ON DELETE CASCADE is powerful but dangerous. Accidentally deleting a parent row can wipe out thousands of child rows silently. Use with caution.

CHECK

Validates that values meet a condition:

sql

CREATE TABLE employees (
    id INTEGER PRIMARY KEY,
    salary DECIMAL(10,2) CHECK (salary > 0),
    age INTEGER CHECK (age >= 16 AND age <= 120),
    department VARCHAR(50) CHECK (department IN ('Engineering', 'Sales', 'HR'))
);

sql

-- This will fail
INSERT INTO employees (salary, age, department)
VALUES (-500, 150, 'Gaming');  -- negative salary, overage, invalid dept

DEFAULT

Sets a value when none is provided:

sql

CREATE TABLE orders (
    id INTEGER PRIMARY KEY,
    status VARCHAR(20) DEFAULT 'pending',
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    currency VARCHAR(3) DEFAULT 'USD'
);

sql

INSERT INTO orders (id) VALUES (1);
-- status = 'pending', created_at = now, currency = 'USD'

All Together: A Well-Designed Table

sql

CREATE TABLE accounts (
    id          INTEGER PRIMARY KEY AUTOINCREMENT,
    username    VARCHAR(50)  NOT NULL UNIQUE,
    email       VARCHAR(255) NOT NULL UNIQUE,
    password_hash VARCHAR(255) NOT NULL,
    role        VARCHAR(20)  NOT NULL DEFAULT 'user'
                    CHECK (role IN ('user', 'admin', 'moderator')),
    is_active   BOOLEAN      NOT NULL DEFAULT TRUE,
    balance     DECIMAL(12,2) NOT NULL DEFAULT 0.00
                    CHECK (balance >= 0),
    created_at  TIMESTAMP    NOT NULL DEFAULT CURRENT_TIMESTAMP,
    updated_at  TIMESTAMP
);

Real-World Use Case: Preventing Bad Data

sql

CREATE TABLE reviews (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    user_id INTEGER NOT NULL,
    product_id INTEGER NOT NULL,
    rating INTEGER NOT NULL CHECK (rating >= 1 AND rating <= 5),
    title VARCHAR(200),
    body TEXT,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE CASCADE,
    FOREIGN KEY (product_id) REFERENCES products(id) ON DELETE CASCADE,
    UNIQUE (user_id, product_id)  -- one review per user per product
);

This table guarantees:

Rating is always 1-5
No NULL ratings
One review per user per product
If a user/product is deleted, reviews are cleaned up
Review has a creation timestamp

✅Success

Constraints are your first line of defense against bad data. Define them at the database level, not just in your application code. Database constraints apply everywhere: even if someone writes a buggy INSERT or connects from a different tool.

Practice Questions

What data type should you use for a column storing product prices? Why?
Write a CREATE TABLE statement for students with: id (PK), email (unique, not null), age (check 0-150), enrollment_date (default today).
What is the difference between CHAR(10) and VARCHAR(10)?
What does ON DELETE CASCADE do? Give an example where it's appropriate.
Write a CHECK constraint that ensures a discount column is between 0 and 100 (inclusive).
Can a table have multiple PRIMARY KEY constraints? Can it have multiple UNIQUE constraints?
What happens to child rows when a parent row is deleted with ON DELETE SET NULL?
Write a table enrollments with a composite primary key on (student_id, course_id) and foreign keys to both tables.
Why should you avoid FLOAT for monetary columns?
What is the storage difference between INTEGER and SMALLINT? When would you choose one over the other?

Progress70%

CREATE, ALTER, and DROP Tables

GROUP BY and HAVING, Grouping and Filtering Aggregates

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Course Content

1. What is SQL and Relational Databases?2. Database Design Basics and Normalization 3. SELECT and WHERE: Querying Data 4. Ordering, Limiting, and Aliasing Results 5. INSERT, UPDATE, DELETE, Data Manipulation 6. CREATE, ALTER, and DROP Tables 7. SQL Data Types and Constraints 8. GROUP BY and HAVING, Grouping and Filtering Aggregates 9. Advanced Aggregate Functions 10. Capstone Project: Library Database