SQL Constraints: CHECK & DEFAULT – Setting Rules and Defaults for Your Data

SQL isn’t just about storing data — it’s also about making sure that data follows the rules. That’s where CHECK and DEFAULT come in.

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🔧 Quick Syntax

CREATE TABLE table_name (
    column_name datatype CHECK (condition),
    column_name datatype DEFAULT default_value
);

DEFAULT – Add a Value Automatically When None is Given

Sometimes, users forget to enter something… or maybe you just want to give them a starting value. That’s what DEFAULT is for!

Syntax Example

CREATE TABLE users (
    username VARCHAR(50),
    is_active BOOLEAN DEFAULT TRUE
);

This says: “If no value is provided for is_active, automatically use TRUE.”

Why Use DEFAULT?

• Saves time and reduces errors
• Ensures consistency for missing values
• Perfect for things like:
  • created_at timestamps
  • status fields
  • Flags like is_active, is_admin, etc.

⚙️ How It Works in Practice

INSERT INTO users (username) VALUES ('maria');

The result:

username	is_active
maria	true

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CHECK – Enforce a Rule on Column Values

CHECK is like setting a rule or filter for a column. It makes sure that only data that meets the condition gets in.

Syntax Example

CREATE TABLE products (
    name VARCHAR(100),
    price DECIMAL(10, 2) CHECK (price > 0)
);

This says: “Only allow prices that are greater than 0.”

What Happens If You Break the Rule?

INSERT INTO products (name, price) VALUES ('Mousepad', -5);

This will fail. Why? Because -5 does not pass the CHECK (price > 0) condition.

Common Uses for CHECK

• Making sure a value falls within a range:
  • Age must be greater than 0
  • Rating between 1 and 5
• Validating simple business rules:
  • Quantity can’t be negative
  • Salary must be above minimum wage

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Recap

Constraint	What It Does	Use It When…
DEFAULT	Inserts a value automatically when none is given	You want a fallback value
CHECK	Makes sure a value meets a specific condition	You need to enforce a rule or range

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Final Thoughts

SQL constraints like DEFAULT and CHECK help your database be smarter and safer — setting smart defaults and stopping bad data at the door. Combine them with NOT NULL, UNIQUE, and PRIMARY KEY, and you’ve got rock-solid tables.