PostgreSQL vs MySQL: Which Database for Your Project?
Comprehensive comparison of the two most popular relational databases. Features, performance and use cases in detail.

PostgreSQL vs MySQL: The Ultimate Database Comparison
PostgreSQL and MySQL are the two dominant open-source databases. Both are mature, performant, and widely used. But they have different strengths – here's how to determine which is right for your project.
The Basics
PostgreSQL
- Type: Object-relational database
- License: PostgreSQL License (very permissive)
- Initial Release: 1996
- Philosophy: Feature richness and standards compliance
MySQL
- Type: Relational database
- License: GPL (+ commercial license from Oracle)
- Initial Release: 1995
- Philosophy: Simplicity and performance
Feature Comparison
| Feature | PostgreSQL | MySQL |
|---|---|---|
| ACID Compliance | Full | Full (with InnoDB) |
| JSON Support | Native (JSONB) | JSON data type |
| Full-Text Search | Built-in | Built-in |
| Replication | Streaming + Logical | Master-Slave, Group |
| Partitioning | Declarative | Range, List, Hash |
| Stored Procedures | PL/pgSQL, Python, Perl | SQL/PSM |
| Materialized Views | Yes | No |
| Foreign Data Wrappers | Yes | No |
| Window Functions | Comprehensive | Since 8.0 |
| CTEs (WITH) | Recursive | Since 8.0 |
When to Choose PostgreSQL?
1. Complex Queries
PostgreSQL excels at complex analytical queries:
-- Hierarchical query with recursive CTE WITH RECURSIVE org_tree AS ( SELECT id, name, manager_id, 1 AS level FROM employees WHERE manager_id IS NULL UNION ALL SELECT e.id, e.name, e.manager_id, ot.level + 1 FROM employees e JOIN org_tree ot ON e.manager_id = ot.id ) SELECT * FROM org_tree ORDER BY level, name; -- Window Functions for ranking SELECT product_name, category, price, RANK() OVER (PARTITION BY category ORDER BY price DESC) as price_rank, AVG(price) OVER (PARTITION BY category) as avg_category_price FROM products;
2. JSON Data
PostgreSQL's JSONB is optimized for semi-structured data:
-- JSONB column with index CREATE TABLE orders ( id SERIAL PRIMARY KEY, customer_id INT, items JSONB, created_at TIMESTAMPTZ DEFAULT NOW() ); -- GIN index for fast JSON search CREATE INDEX idx_orders_items ON orders USING GIN (items); -- Query JSON data SELECT * FROM orders WHERE items @> '[{"product_id": 123}]'; -- Aggregate JSON SELECT customer_id, jsonb_agg(items) as all_items FROM orders GROUP BY customer_id;
3. Geospatial (PostGIS)
With PostGIS, PostgreSQL leads for geodata:
-- Enable PostGIS CREATE EXTENSION postgis; -- Locations with geometry CREATE TABLE locations ( id SERIAL PRIMARY KEY, name VARCHAR(100), geom GEOMETRY(Point, 4326) ); -- All locations within 5km radius SELECT name, ST_Distance(geom, 'POINT(-0.1276 51.5074)'::geography) as distance FROM locations WHERE ST_DWithin(geom, 'POINT(-0.1276 51.5074)'::geography, 5000) ORDER BY distance;
4. Data Integrity
PostgreSQL offers comprehensive constraints:
-- Partial Unique Constraints CREATE UNIQUE INDEX idx_active_subscription ON subscriptions (user_id) WHERE status = 'active'; -- Check Constraints ALTER TABLE products ADD CONSTRAINT price_positive CHECK (price > 0); -- Exclusion Constraints (no overlap) CREATE TABLE reservations ( room_id INT, during TSTZRANGE, EXCLUDE USING GIST (room_id WITH =, during WITH &&) );
When to Choose MySQL?
1. Simple CRUD Operations
MySQL is optimized for fast read/write operations:
-- Simple queries are very fast SELECT * FROM users WHERE id = 12345; SELECT * FROM products WHERE category_id = 5 LIMIT 20; -- Bulk Inserts INSERT INTO logs (message, level, created_at) VALUES ('Request processed', 'INFO', NOW()), ('Cache hit', 'DEBUG', NOW()), ('Response sent', 'INFO', NOW());
2. Web Applications (LAMP Stack)
MySQL integrates perfectly with:
- WordPress
- Drupal
- Magento
- Laravel
- Ruby on Rails
// PHP with MySQL $pdo = new PDO('mysql:host=localhost;dbname=app', 'user', 'pass'); $stmt = $pdo->prepare('SELECT * FROM posts WHERE author_id = ?'); $stmt->execute([$authorId]); $posts = $stmt->fetchAll(PDO::FETCH_ASSOC);
3. Read-Heavy Workloads
MySQL's read replication is easy to set up:
-- On the Master SHOW MASTER STATUS; -- On the Replica CHANGE REPLICATION SOURCE TO SOURCE_HOST='master.example.com', SOURCE_USER='repl_user', SOURCE_PASSWORD='password', SOURCE_LOG_FILE='mysql-bin.000001', SOURCE_LOG_POS=12345; START REPLICA;
4. Managed Services
Nearly all cloud providers offer MySQL:
- AWS RDS, Aurora MySQL
- Google Cloud SQL
- Azure Database for MySQL
- PlanetScale (Vitess-based)
Performance Comparison
Benchmarks (typical results)
| Scenario | PostgreSQL | MySQL |
|---|---|---|
| Simple SELECT by PK | 95k QPS | 110k QPS |
| Complex JOINs | Faster | Slower |
| Bulk INSERT | 50k/s | 70k/s |
| JSON Operations | Faster | Slower |
| Concurrent Writes | Better | MVCC overhead |
Important: Benchmarks vary greatly depending on configuration, hardware, and use case. Test with your real data!
Migration Between Systems
From MySQL to PostgreSQL
# With pgloader pgloader mysql://user:pass@localhost/dbname \ postgresql://user:pass@localhost/newdb # Or manually: # 1. Export schema mysqldump --no-data dbname > schema.sql # 2. Convert schema (adjust data types) # INT AUTO_INCREMENT → SERIAL # DATETIME → TIMESTAMP # TINYINT(1) → BOOLEAN # TEXT/MEDIUMTEXT/LONGTEXT → TEXT # 3. Export/import data mysqldump --no-create-info --complete-insert dbname > data.sql psql newdb < data.sql
Important Differences When Migrating
| MySQL | PostgreSQL |
|---|---|
| ``` backticks | "double quotes" |
| AUTO_INCREMENT | SERIAL / IDENTITY |
| LIMIT 10, 20 | LIMIT 20 OFFSET 10 |
| NOW() | NOW() / CURRENT_TIMESTAMP |
| IFNULL() | COALESCE() |
| GROUP_CONCAT() | STRING_AGG() |
| ENUM('a','b') | CREATE TYPE ... AS ENUM |
ORM Support
Both databases are supported by all major ORMs:
Node.js (Prisma)
// prisma/schema.prisma datasource db { provider = "postgresql" // or "mysql" url = env("DATABASE_URL") } model User { id Int @id @default(autoincrement()) email String @unique posts Post[] } // Same code for both databases const users = await prisma.user.findMany({ include: { posts: true } });
Python (SQLAlchemy)
from sqlalchemy import create_engine # PostgreSQL engine = create_engine('postgresql://user:pass@localhost/db') # MySQL engine = create_engine('mysql+pymysql://user:pass@localhost/db') # Rest of the code remains identical
Hosting Options
PostgreSQL
| Provider | Specialty |
|---|---|
| Supabase | Firebase alternative with Postgres |
| Neon | Serverless, Branching |
| Railway | Simple deployment |
| AWS RDS | Enterprise-ready |
| Render | Free tier |
MySQL
| Provider | Specialty |
|---|---|
| PlanetScale | Serverless, Git-like Branching |
| AWS Aurora | MySQL-compatible, highly available |
| DigitalOcean | Simple Managed DB |
| Vitess | Horizontal Scaling |
Conclusion and Recommendation
PostgreSQL when:
- Complex data models and queries
- JSON data is important
- Geodata is needed
- Data integrity is highest priority
- You want to use advanced SQL features
MySQL when:
- Simple CRUD applications
- Existing MySQL expertise in team
- WordPress/Drupal/Magento
- Maximum read performance required
- Broad cloud support important
Our Practice at Balane Tech
We primarily use PostgreSQL for:
- New projects
- Complex business logic
- Applications with JSON data
We use MySQL for:
- Existing WordPress projects
- Client requirement for MySQL
- Simple web applications
Both databases are excellent. The "right" choice depends on your specific requirements.


