MySQL vs PostgreSQL: Choosing the Right Database

Choosing between MySQL and PostgreSQL is one of the most common database decisions developers face. After working extensively with both in production, I’ve learned that the “best” choice depends heavily on your specific use case. Here’s an honest comparison based on real-world experience.

Quick Comparison

Feature	MySQL	PostgreSQL
License	GPL/Commercial	PostgreSQL License (BSD-like)
ACID Compliance	Yes (InnoDB)	Yes
JSON Support	5.7+	9.2+ (Better)
Full-Text Search	Basic	Advanced (tsvector)
Window Functions	8.0+	9.0+
Replication	Master-Slave	Streaming Replication
Performance	Fast reads	Complex queries

Performance Characteristics

MySQL Strengths

MySQL excels at:

• Simple read-heavy workloads
• High concurrency for simple queries
• Replication for read scaling

-- MySQL handles simple queries very well
SELECT * FROM users WHERE email = 'user@example.com';
-- Uses index efficiently, very fast

-- Simple aggregations
SELECT COUNT(*) FROM orders WHERE status = 'completed';
-- Optimized for this pattern

PostgreSQL Strengths

PostgreSQL excels at:

• Complex queries and joins
• Data integrity and constraints
• Advanced data types

-- PostgreSQL handles complex queries better
WITH user_stats AS (
    SELECT 
        u.id,
        COUNT(o.id) as order_count,
        SUM(o.total) as total_spent,
        AVG(o.total) as avg_order_value
    FROM users u
    LEFT JOIN orders o ON u.id = o.user_id
    WHERE u.created_at > '2016-01-01'
    GROUP BY u.id
)
SELECT 
    u.*,
    us.order_count,
    us.total_spent,
    us.avg_order_value,
    CASE 
        WHEN us.total_spent > 1000 THEN 'VIP'
        WHEN us.total_spent > 500 THEN 'Premium'
        ELSE 'Standard'
    END as customer_tier
FROM users u
JOIN user_stats us ON u.id = us.id
ORDER BY us.total_spent DESC;
-- PostgreSQL's query planner optimizes this better

Feature Comparison

JSON Support

MySQL 5.7+ JSON:

-- MySQL JSON
CREATE TABLE products (
    id INT PRIMARY KEY,
    name VARCHAR(255),
    attributes JSON
);

INSERT INTO products VALUES (
    1,
    'Laptop',
    '{"brand": "Dell", "ram": "16GB", "storage": "512GB"}'
);

-- Query JSON
SELECT * FROM products 
WHERE JSON_EXTRACT(attributes, '$.ram') = '16GB';

-- Index JSON
ALTER TABLE products 
ADD INDEX idx_ram ((CAST(attributes->>'$.ram' AS CHAR(10))));

PostgreSQL JSONB:

-- PostgreSQL JSONB (more efficient)
CREATE TABLE products (
    id SERIAL PRIMARY KEY,
    name VARCHAR(255),
    attributes JSONB
);

INSERT INTO products VALUES (
    1,
    'Laptop',
    '{"brand": "Dell", "ram": "16GB", "storage": "512GB"}'::jsonb
);

-- Query JSONB (more powerful)
SELECT * FROM products 
WHERE attributes @> '{"ram": "16GB"}';

-- Index JSONB (GIN index)
CREATE INDEX idx_attributes ON products USING GIN (attributes);

-- Advanced queries
SELECT * FROM products 
WHERE attributes ? 'ram'  -- Key exists
AND attributes->>'brand' = 'Dell';

Winner: PostgreSQL - JSONB is more efficient and feature-rich.

Full-Text Search

MySQL Full-Text:

-- MySQL full-text search
ALTER TABLE articles ADD FULLTEXT(title, content);

SELECT * FROM articles 
WHERE MATCH(title, content) AGAINST('database performance' IN NATURAL LANGUAGE MODE);

PostgreSQL Full-Text:

-- PostgreSQL full-text search (more powerful)
ALTER TABLE articles ADD COLUMN search_vector tsvector;

CREATE INDEX idx_search ON articles USING GIN(search_vector);

-- Update search vector
UPDATE articles SET search_vector = 
    to_tsvector('english', coalesce(title, '') || ' ' || coalesce(content, ''));

-- Search with ranking
SELECT 
    title,
    ts_rank(search_vector, query) AS rank
FROM articles, to_tsquery('english', 'database & performance') query
WHERE search_vector @@ query
ORDER BY rank DESC;

Winner: PostgreSQL - More flexible and powerful.

Use Case Recommendations

Choose MySQL When:

1. Simple web applications
   • Blog, CMS, simple e-commerce
   • Read-heavy workloads
   • Team familiar with MySQL
2. High read concurrency
   • Simple queries with many concurrent reads
   • MySQL’s connection handling is excellent

Choose PostgreSQL When:

1. Complex applications
   • Data analytics
   • Complex reporting
   • Financial systems
2. Data integrity critical
   • Stronger constraints
   • Better ACID compliance
   • More validation options

Conclusion

Choose MySQL if:

• Simple application
• High read concurrency with simple queries
• Team familiar with MySQL

Choose PostgreSQL if:

• Complex queries and reporting
• Need advanced features (JSON, full-text, arrays)
• Data integrity is critical

Both are excellent databases. The choice often comes down to your specific needs and team expertise.

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Comparison based on MySQL 5.7 and PostgreSQL 9.5, reflecting the state of both databases in mid-2016.