MySQL vs PostgreSQL: Key Differences

When diving into the world of relational databases, developers often find themselves choosing between MySQL and PostgreSQL. Both are powerful, open-source database management systems, but they handle certain operations quite differently. This comprehensive guide will explore these differences, focusing particularly on query syntax and functionality.

Contents

Historical Context and Philosophy

MySQL, originally developed by MySQL AB and now owned by Oracle, was designed with speed and simplicity in mind. Its initial focus was on web applications that primarily needed quick reads and basic write operations. PostgreSQL, developed at the University of California, Berkeley, emerged from the POSTGRES project with a focus on extensibility and standards compliance. These different origins have shaped how each database handles various operations.

Data Types and Their Implementations

Let’s examine how these databases handle different data types, as this affects how we write queries and structure our data.

MySQL Data Types

MySQL offers straightforward data types that prioritize performance:

CREATE TABLE product_inventory (
    id INT AUTO_INCREMENT PRIMARY KEY,
    name VARCHAR(255),
    price DECIMAL(10,2),
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    tags JSON,
    is_available TINYINT(1)
);

PostgreSQL Data Types

PostgreSQL provides more sophisticated data types with additional functionality:

CREATE TABLE product_inventory (
    id SERIAL PRIMARY KEY,
    name VARCHAR(255),
    price DECIMAL(10,2),
    created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
    tags JSONB,
    is_available BOOLEAN
);

Notice how PostgreSQL uses SERIAL instead of AUTO_INCREMENT, BOOLEAN instead of TINYINT(1), and JSONB for more efficient JSON storage.

Key Syntax Differences

Case Sensitivity

MySQL treats table and column names as case-insensitive on Windows and case-sensitive on Unix-based systems. PostgreSQL is always case-sensitive and typically uses lowercase by default. Here’s how this affects queries:

MySQL:

SELECT * FROM Users;
SELECT * FROM users;
-- Both queries work the same on Windows

PostgreSQL:

SELECT * FROM "Users"; -- Looks for exactly "Users"
SELECT * FROM users;   -- Looks for exactly "users"
-- These are different queries

String Comparisons

String comparison behavior differs significantly between the two databases:

MySQL:

SELECT * FROM customers 
WHERE name LIKE 'john%'; -- Case-insensitive by default

PostgreSQL:

SELECT * FROM customers 
WHERE name LIKE 'john%'; -- Case-sensitive by default
SELECT * FROM customers 
WHERE name ILIKE 'john%'; -- Case-insensitive using ILIKE

UPSERT Operations

Both databases handle upsert operations (insert or update if exists) differently:

MySQL:

INSERT INTO products (id, name, price)
VALUES (1, 'Widget', 19.99)
ON DUPLICATE KEY UPDATE
    name = VALUES(name),
    price = VALUES(price);

PostgreSQL:

INSERT INTO products (id, name, price)
VALUES (1, 'Widget', 19.99)
ON CONFLICT (id) DO UPDATE
    SET name = EXCLUDED.name,
        price = EXCLUDED.price;

Advanced Features and Their Syntax

Working with JSON

Both databases support JSON, but with different approaches:

MySQL:

-- Extracting JSON data
SELECT JSON_EXTRACT(data, '$.name') AS name
FROM users;

-- Updating JSON data
UPDATE users 
SET data = JSON_SET(data, '$.name', 'New Name')
WHERE id = 1;

PostgreSQL:

-- Extracting JSON data
SELECT data->>'name' AS name
FROM users;

-- Updating JSON data
UPDATE users 
SET data = jsonb_set(data, '{name}', '"New Name"')
WHERE id = 1;

Full-Text Search

Full-text search capabilities show significant differences:

MySQL:

-- Creating a fulltext index
ALTER TABLE articles 
ADD FULLTEXT INDEX idx_content (content);

-- Performing a full-text search
SELECT * FROM articles 
WHERE MATCH(content) AGAINST('search terms' IN NATURAL LANGUAGE MODE);

PostgreSQL:

-- Creating a text search vector
ALTER TABLE articles 
ADD COLUMN content_tsv tsvector;

UPDATE articles 
SET content_tsv = to_tsvector('english', content);

CREATE INDEX idx_content ON articles USING GIN (content_tsv);

-- Performing a full-text search
SELECT * FROM articles 
WHERE content_tsv @@ to_tsquery('english', 'search & terms');

Window Functions

While both databases support window functions, PostgreSQL offers more features:

MySQL:

SELECT 
    department,
    employee_name,
    salary,
    RANK() OVER (PARTITION BY department ORDER BY salary DESC) as salary_rank
FROM employees;

PostgreSQL:

SELECT 
    department,
    employee_name,
    salary,
    RANK() OVER (PARTITION BY department ORDER BY salary DESC) as salary_rank,
    PERCENT_RANK() OVER (PARTITION BY department ORDER BY salary DESC) as salary_percentile,
    FIRST_VALUE(employee_name) OVER (
        PARTITION BY department 
        ORDER BY salary DESC 
        RANGE BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING
    ) as highest_paid
FROM employees;

Performance Considerations

The way queries are written can significantly impact performance in each database. Here are some key considerations:

Indexing Syntax

MySQL:

-- Creating a standard index
CREATE INDEX idx_name ON users(name);

-- Creating a composite index
CREATE INDEX idx_name_email ON users(name, email);

PostgreSQL:

-- Creating a standard index
CREATE INDEX idx_name ON users USING btree (name);

-- Creating a composite index
CREATE INDEX idx_name_email ON users USING btree (name, email);

-- Creating a partial index (PostgreSQL specific)
CREATE INDEX idx_active_users ON users (name) 
WHERE active = true;

Query Optimization

Both databases have different query planners and optimization strategies. Here’s how to view execution plans:

MySQL:

EXPLAIN SELECT * FROM users 
WHERE name = 'John' 
AND email LIKE '%@example.com';

PostgreSQL:

EXPLAIN ANALYZE SELECT * FROM users 
WHERE name = 'John' 
AND email LIKE '%@example.com';

PostgreSQL’s EXPLAIN ANALYZE provides more detailed execution information, including actual timing data.

Conclusion

While MySQL and PostgreSQL share many similarities as relational databases, their different philosophies and implementations lead to distinct approaches in query writing and optimization. MySQL often provides simpler syntax and faster performance for basic operations, while PostgreSQL offers more advanced features and stricter data integrity controls.

When choosing between them, consider your specific needs:

Choose MySQL if you need:

Simple setup and maintenance
Fast read operations
Basic CRUD operations
Compatibility with common web frameworks

Choose PostgreSQL if you need:

Complex queries and operations
Strong data integrity
Advanced JSON operations
Custom data types and functions
Complex full-text search capabilities

Remember that these differences in query syntax and functionality reflect deeper architectural choices in each database system. Understanding these differences helps in writing more efficient and effective queries for your chosen database.