Subqueries vs Joins: When to Use Each in SQL

Table of Contents

1. Introduction
2. What is a Subquery?
3. What is a Join?
4. Syntax Comparison: Subquery vs Join
5. When to Use Subqueries
6. When to Use Joins
7. Types of Subqueries
8. Types of Joins
9. Performance Considerations
10. Readability and Maintainability
11. Real-World Example: Orders and Customers
12. Filtering with Subqueries
13. Filtering with Joins
14. Aggregations in Subqueries vs Joins
15. Correlated Subqueries vs Joins
16. Nested Joins vs Nested Subqueries
17. Combining Subqueries with Joins
18. Common Mistakes
19. Best Practices
20. Summary and What’s Next

1. Introduction

In SQL, there are often multiple ways to solve the same problem. Two of the most powerful and flexible techniques are subqueries and joins. Understanding when to use each leads to cleaner, faster, and more maintainable queries.

2. What is a Subquery?

A subquery is a SQL query nested inside another query. It can return a single value, a list of values, or even a complete table.

Example:

sqlCopyEditSELECT name FROM customers
WHERE id IN (SELECT customer_id FROM orders WHERE total > 1000);

3. What is a Join?

A join combines rows from two or more tables based on a related column between them, usually a foreign key.

Example:

sqlCopyEditSELECT c.name, o.total
FROM customers c
JOIN orders o ON c.id = o.customer_id
WHERE o.total > 1000;

4. Syntax Comparison: Subquery vs Join

5. When to Use Subqueries

✅ Use subqueries when:

• You need to filter based on an aggregated value
• The logic is better modularized in a separate query
• The outer query should depend on dynamic values from inner query
• You want encapsulation for readability

6. When to Use Joins

✅ Use joins when:

• You want to retrieve data from multiple tables
• You need columns from more than one table
• You’re writing reporting, dashboards, or summaries
• You need high-performance queries (joins are often faster)

7. Types of Subqueries

8. Types of Joins

9. Performance Considerations

Note: Correlated subqueries can be significantly slower on large datasets.

10. Readability and Maintainability

• Subqueries improve modularity: Ideal for breaking logic into steps
• Joins improve transparency: Ideal for combining related entities into reports
• Deeply nested subqueries may reduce readability
• Multi-join queries may be hard to follow without aliases and comments

11. Real-World Example: Orders and Customers

With JOIN:

sqlCopyEditSELECT c.name, o.total
FROM customers c
JOIN orders o ON c.id = o.customer_id;

With Subquery:

sqlCopyEditSELECT name
FROM customers
WHERE id IN (SELECT customer_id FROM orders);

Choose JOIN if you need customer and order data; use a subquery if you only need to check presence or filter.

12. Filtering with Subqueries

sqlCopyEditSELECT name FROM employees
WHERE salary > (
  SELECT AVG(salary) FROM employees
);

Useful for comparing values to aggregates.

13. Filtering with Joins

sqlCopyEditSELECT e.name
FROM employees e
JOIN (
  SELECT department_id, AVG(salary) AS avg_salary
  FROM employees
  GROUP BY department_id
) dept_avg ON e.department_id = dept_avg.department_id
WHERE e.salary > dept_avg.avg_salary;

More flexible and readable for grouped comparisons.

14. Aggregations in Subqueries vs Joins

Subquery:

sqlCopyEditSELECT name
FROM products
WHERE price > (SELECT AVG(price) FROM products);

Join:

sqlCopyEditSELECT p.name
FROM products p
JOIN (
  SELECT AVG(price) AS avg_price FROM products
) avg_table ON 1=1
WHERE p.price > avg_table.avg_price;

Both return the same — choose based on preference or reusability.

15. Correlated Subqueries vs Joins

sqlCopyEdit-- Correlated subquery
SELECT name
FROM employees e
WHERE salary > (
  SELECT AVG(salary)
  FROM employees
  WHERE department = e.department
);

Join equivalent:

sqlCopyEditSELECT e.name
FROM employees e
JOIN (
  SELECT department, AVG(salary) AS avg_salary
  FROM employees
  GROUP BY department
) dept_avg ON e.department = dept_avg.department
WHERE e.salary > dept_avg.avg_salary;

Joins are usually faster and easier to debug.

16. Nested Joins vs Nested Subqueries

• Nested joins: Multiple joins between multiple tables — great for flat data retrieval
• Nested subqueries: Good for step-by-step data transformation, particularly when isolation is required

17. Combining Subqueries with Joins

sqlCopyEditSELECT u.name, o.total
FROM users u
JOIN (
  SELECT * FROM orders WHERE total > 500
) o ON u.id = o.user_id;

This filters orders first using a subquery, then joins to users.

18. Common Mistakes

19. Best Practices

• Use joins when retrieving fields from multiple tables
• Use subqueries for filters, aggregates, and modular logic
• Avoid correlated subqueries for large datasets
• Always benchmark performance when query speed matters
• Use descriptive aliases in joins and subqueries

20. Summary and What’s Next

Both subqueries and joins are foundational SQL techniques. Subqueries shine in filtering and encapsulated logic, while joins are better for combining related data. A skilled SQL developer knows when to use which — based on performance, readability, and the task at hand.