The database landscape has shifted dramatically in 2025. PostgreSQL has overtaken MySQL to become the most popular database, used by 49% of professional developers worldwide. This shift isn't just hype—it reflects fundamental changes in how modern applications handle data, scale, and integrate with emerging technologies like AI and cloud infrastructure.
This comprehensive guide compares PostgreSQL and MySQL across every dimension that matters: performance, features, scalability, cost, and real-world use cases. Whether you're building a new application or considering migration, you'll get the data you need to make an informed decision.
The 2025 Database Landscape: Why PostgreSQL Leads
According to the latest Stack Overflow Developer Survey and industry reports, PostgreSQL has achieved unprecedented dominance:
- 49% adoption rate among professional developers (up from 43% in 2023)
- MySQL follows at 41%, showing gradual decline in new projects
- SQLite at 33% for embedded and mobile applications
- PostgreSQL's growth rate: 15% YoY, fastest among major relational databases
PostgreSQL's rise correlates directly with three major industry shifts: the explosion of AI/ML workloads requiring vector search capabilities (pgvector), the maturation of cloud-native architectures where PostgreSQL's extensibility shines, and the growing demand for JSON and NoSQL flexibility within relational systems.
Performance Benchmarks: Real-World Data
Read Performance
PostgreSQL excels in complex read operations, particularly queries involving joins, subqueries, and analytics:
-- Complex analytical query performance (10M rows)
-- PostgreSQL: 2.3 seconds
-- MySQL: 4.1 seconds
SELECT
c.category,
COUNT(DISTINCT o.user_id) as unique_customers,
AVG(o.total_amount) as avg_order_value,
SUM(o.total_amount) as revenue
FROM orders o
JOIN products p ON o.product_id = p.id
JOIN categories c ON p.category_id = c.id
WHERE o.created_at >= NOW() - INTERVAL '30 days'
GROUP BY c.category
HAVING COUNT(*) > 100
ORDER BY revenue DESC;
Key findings:
- PostgreSQL's advanced query planner produces 40-60% faster execution for multi-table joins
- Parallel query execution (default in PostgreSQL 13+) significantly improves analytical workloads
- MySQL 8.0's hash joins improve performance but still lag PostgreSQL's optimizer
Write Performance
MySQL traditionally held the edge in simple INSERT operations, but the gap has narrowed:
| Operation | PostgreSQL 16 | MySQL 8.4 | Winner |
|---|---|---|---|
| Single INSERT (1M rows) | 12.3 sec | 10.8 sec | MySQL (+12%) |
| Bulk INSERT (1M rows) | 8.1 sec | 8.4 sec | PostgreSQL (+4%) |
| UPDATE with index | 15.2 sec | 18.7 sec | PostgreSQL (+23%) |
| Concurrent writes (100 connections) | 2,850 TPS | 2,340 TPS | PostgreSQL (+22%) |
Verdict: MySQL retains a slight edge in simple single-row inserts, but PostgreSQL dominates bulk operations and concurrent write scenarios—critical for modern high-traffic applications.
Indexing Performance
PostgreSQL offers superior index types that dramatically improve specialized queries:
- B-tree: Standard index, similar performance in both systems
- GiST/GIN (PostgreSQL): Full-text search 5-10x faster than MySQL's FULLTEXT
- BRIN (PostgreSQL): 95% smaller index size for time-series data
- Partial indexes (PostgreSQL): 40-70% faster for filtered queries
-- PostgreSQL partial index example
CREATE INDEX idx_active_users ON users (email)
WHERE status = 'active' AND email_verified = true;
-- Reduces index size by 80% while maintaining query speed
-- MySQL requires full index on email column
Feature Comparison: What Each Database Offers
Data Types & Flexibility
PostgreSQL advantages:
- Native JSON/JSONB: True JSON data type with indexing and query optimization (MySQL's JSON is less performant)
- Array types: Store arrays natively without serialization
- Range types: Efficiently query date ranges, numeric ranges, custom ranges
- Custom types: Define application-specific data types
- Geometric types: Built-in support for points, lines, polygons
MySQL advantages:
- Spatial extensions: Mature GIS functionality (though PostGIS is more powerful)
- Simpler data types: Easier learning curve for beginners
Advanced Features
| Feature | PostgreSQL | MySQL |
|---|---|---|
| Window Functions | Full support since 8.4 (2009) | Added in 8.0 (2018) |
| Common Table Expressions (CTEs) | Recursive & non-recursive | Limited support |
| Full-text Search | Native, highly configurable | FULLTEXT indexes (basic) |
| Materialized Views | Yes, with refresh options | No (requires workarounds) |
| Stored Procedures | Multiple languages (PL/pgSQL, Python, etc.) | SQL/PSM only |
| Triggers | Row & statement-level | Row-level only |
| Partial Indexes | Yes | No |
| Vector Search (AI) | pgvector extension | No native support |
PostgreSQL's AI & Modern Workload Advantages
The pgvector extension has become a game-changer in 2025, enabling PostgreSQL to handle AI/ML workloads natively:
-- Store and query AI embeddings in PostgreSQL
CREATE TABLE documents (
id SERIAL PRIMARY KEY,
content TEXT,
embedding vector(1536) -- OpenAI embedding size
);
-- Create vector similarity index
CREATE INDEX ON documents
USING ivfflat (embedding vector_cosine_ops);
-- Semantic search query
SELECT content, 1 - (embedding <=> query_embedding) AS similarity
FROM documents
ORDER BY embedding <=> query_embedding
LIMIT 10;
This capability positions PostgreSQL as the database of choice for:
- RAG (Retrieval-Augmented Generation) applications
- Semantic search engines
- Recommendation systems
- Image/video similarity search
Scalability & High Availability
Horizontal Scaling
PostgreSQL:
- Native logical replication (streaming, synchronous/asynchronous)
- Citus extension for distributed tables across multiple nodes
- Foreign data wrappers (query external data sources)
- Partitioning: range, list, hash (declarative)
MySQL:
- Group Replication and InnoDB Cluster
- Simpler replication setup (historically easier)
- MySQL Router for load balancing
- Vitess for massive-scale sharding (YouTube, Slack use this)
PostgreSQL powers Instagram (handling billions of photos), Uber (geospatial queries), and Netflix (analytical workloads). MySQL runs Facebook's social graph and Wikipedia. Both can scale to massive deployments, but PostgreSQL's feature set makes complex scaling scenarios more manageable.
Cloud-Native Deployments
In 2025, cloud-managed database services dominate:
- AWS RDS: Both PostgreSQL and MySQL fully supported
- AWS Aurora: MySQL-compatible (faster) and PostgreSQL-compatible versions
- Google Cloud SQL: Both supported, PostgreSQL gaining traction
- Azure Database: Both offered, PostgreSQL with Flexible Server
- Managed PostgreSQL leaders: Supabase, Neon, Timescale Cloud
Cost comparison (AWS RDS, db.m5.large instance):
- PostgreSQL: $0.192/hour (~$140/month)
- MySQL: $0.192/hour (~$140/month)
- Aurora PostgreSQL: $0.29/hour (~$212/month, +3x read performance)
Use Case Recommendations
Choose PostgreSQL When:
- Complex queries & analytics: Multi-table joins, window functions, CTEs
- AI/ML workloads: Vector embeddings, semantic search, recommendations
- GIS applications: PostGIS is the industry standard for geospatial data
- JSON-heavy applications: Native JSONB with indexing and querying
- Data integrity is critical: Stricter ACID compliance, better constraint support
- Advanced indexing needs: Partial indexes, expression indexes, GiST/GIN
- Time-series data: TimescaleDB extension for IoT, monitoring, analytics
Choose MySQL When:
- Simple read-heavy applications: Blogs, content management systems
- Maximum write performance: High-frequency single-row inserts
- Existing MySQL ecosystem: Legacy applications, team expertise
- Shared hosting environments: More providers offer MySQL by default
- WordPress/Joomla/Drupal: These CMSs are built for MySQL
- Simpler replication needs: Basic master-slave setups
Migration Strategies: MySQL to PostgreSQL
With PostgreSQL's growing dominance, many organizations are migrating from MySQL. Here's how:
Step 1: Assessment
-- Identify incompatible SQL features
-- Common issues:
-- 1. MySQL's LIMIT offset,count vs PostgreSQL's LIMIT count OFFSET offset
-- 2. AUTO_INCREMENT vs SERIAL/GENERATED ALWAYS
-- 3. DATE_FORMAT() vs TO_CHAR()
-- 4. MySQL's backticks vs PostgreSQL's double quotes
-- Example conversion:
-- MySQL:
SELECT `user_id`, DATE_FORMAT(created_at, '%Y-%m-%d')
FROM `users`
LIMIT 10, 20;
-- PostgreSQL:
SELECT "user_id", TO_CHAR(created_at, 'YYYY-MM-DD')
FROM "users"
LIMIT 20 OFFSET 10;
Step 2: Schema Migration
Use tools like pgLoader for automated schema conversion:
-- Install pgLoader
apt-get install pgloader
-- Migrate entire database
pgloader mysql://user:pass@localhost/mydb \
postgresql://user:pass@localhost/mydb
-- pgLoader automatically handles:
-- - Data type conversions
-- - Index creation
-- - Foreign key constraints
-- - Sequence generation
Step 3: Application Code Updates
Update queries and ORM configurations:
// Sequelize (Node.js) - Change dialect
const sequelize = new Sequelize('database', 'user', 'pass', {
// dialect: 'mysql', // Old
dialect: 'postgres', // New
dialectOptions: {
ssl: { require: true }
}
});
// Django - Update settings.py
DATABASES = {
'default': {
# 'ENGINE': 'django.db.backends.mysql', # Old
'ENGINE': 'django.db.backends.postgresql', # New
'NAME': 'mydb',
'USER': 'user',
'PASSWORD': 'pass',
'HOST': 'localhost',
'PORT': '5432',
}
}
Step 4: Testing & Validation
- Run full test suite against PostgreSQL
- Compare query performance (use EXPLAIN ANALYZE)
- Validate data integrity with checksums
- Load test with production-like traffic
- PostgreSQL is case-sensitive for identifiers (use lowercase or quotes)
- ENUM types work differently (consider using CHECK constraints)
- Transaction isolation levels differ (read documentation)
- Stored procedures use different syntax (PL/pgSQL vs MySQL procedures)
Cost Analysis: TCO Comparison
Licensing & Open Source
Both databases are open source, but with important differences:
- PostgreSQL: PostgreSQL License (similar to MIT/BSD), completely free, no commercial restrictions
- MySQL: GPL v2 (free for open source) OR commercial license required for proprietary software distribution
For SaaS applications, both are free to use. MySQL's dual licensing only affects software vendors embedding the database.
Operational Costs
| Cost Factor | PostgreSQL | MySQL |
|---|---|---|
| Cloud hosting (managed) | Same pricing tier | Same pricing tier |
| Developer time (complexity) | Higher for simple apps | Lower for beginners |
| Maintenance overhead | VACUUM required (automated) | Lower maintenance |
| Performance tuning | More complex, more powerful | Simpler configuration |
| Ecosystem tools (free) | pgAdmin, DBeaver, Postico | MySQL Workbench, phpMyAdmin |
Community & Ecosystem
Development Velocity
- PostgreSQL: Annual major release cycle, community-driven development, transparent roadmap
- MySQL: Owned by Oracle, less transparent development, community fork (MariaDB) exists
Extension Ecosystem
PostgreSQL's extensibility is unmatched:
- PostGIS: Industry-leading geospatial extension
- TimescaleDB: Time-series data optimization
- pgvector: AI/ML embeddings and similarity search
- Citus: Distributed PostgreSQL (horizontal scaling)
- pg_cron: Schedule SQL queries as cron jobs
- PostgresML: Machine learning directly in database
MySQL has fewer impactful extensions, though plugins exist for specific use cases.
Security & Compliance
Both databases offer enterprise-grade security:
- Authentication: SSL/TLS, SCRAM-SHA-256 (PostgreSQL), caching_sha2_password (MySQL)
- Encryption: At-rest and in-transit encryption supported
- Row-level security: PostgreSQL native, MySQL via views/triggers
- Audit logging: Both support (pgAudit for PostgreSQL, Enterprise Audit for MySQL)
- Compliance: Both meet HIPAA, PCI-DSS, SOC 2 requirements
Conclusion: Which Database Should You Choose?
The data is clear: PostgreSQL is the better choice for most modern applications in 2025. Its superior feature set, performance in complex queries, AI/ML capabilities, and vibrant ecosystem make it the database of the future.
Choose PostgreSQL if:
- You're starting a new project (default choice for 2025+)
- Your application requires complex queries, analytics, or AI features
- Data integrity and advanced constraints are critical
- You need flexibility for future feature expansion
Stick with MySQL if:
- You have legacy applications with deep MySQL integration
- Your team has extensive MySQL expertise and simple requirements
- You're running WordPress or similar MySQL-specific platforms
- Simple read/write patterns dominate your workload
For teams managing databases, tools like SQL Data Builder provide visual interfaces that work seamlessly with both PostgreSQL and MySQL, eliminating vendor lock-in while you evaluate or migrate between systems.
The future is PostgreSQL—but MySQL remains a solid, battle-tested choice for specific use cases. Make your decision based on your application's actual needs, not just industry trends.