Guides & Tutorials

PostgreSQL vs MySQL: Which Database for Your Project?

Comprehensive comparison of the two most popular relational databases. Features, performance and use cases in detail.

Jonas Hottler
January 24, 2025
14 min read time
PostgreSQLMySQLDatenbankSQLBackendDatabase
PostgreSQL vs MySQL: Which Database for Your Project? - Guides & Tutorials | Blog

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

FeaturePostgreSQLMySQL
ACID ComplianceFullFull (with InnoDB)
JSON SupportNative (JSONB)JSON data type
Full-Text SearchBuilt-inBuilt-in
ReplicationStreaming + LogicalMaster-Slave, Group
PartitioningDeclarativeRange, List, Hash
Stored ProceduresPL/pgSQL, Python, PerlSQL/PSM
Materialized ViewsYesNo
Foreign Data WrappersYesNo
Window FunctionsComprehensiveSince 8.0
CTEs (WITH)RecursiveSince 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)

ScenarioPostgreSQLMySQL
Simple SELECT by PK95k QPS110k QPS
Complex JOINsFasterSlower
Bulk INSERT50k/s70k/s
JSON OperationsFasterSlower
Concurrent WritesBetterMVCC 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

MySQLPostgreSQL
``` backticks"double quotes"
AUTO_INCREMENTSERIAL / IDENTITY
LIMIT 10, 20LIMIT 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

ProviderSpecialty
SupabaseFirebase alternative with Postgres
NeonServerless, Branching
RailwaySimple deployment
AWS RDSEnterprise-ready
RenderFree tier

MySQL

ProviderSpecialty
PlanetScaleServerless, Git-like Branching
AWS AuroraMySQL-compatible, highly available
DigitalOceanSimple Managed DB
VitessHorizontal 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.

Tags

PostgreSQLMySQLDatenbankSQLBackendDatabase