A practical comparison of PostgreSQL and MySQL — features, performance, use cases, and when each database is the right choice. Written by a team that uses PostgreSQL for everything (and will tell you when MySQL is better).
PostgreSQL vs MySQL: which is better? PostgreSQL is generally the better choice for new projects in 2026 due to its superior handling of complex queries, JSON data, full-text search, and advanced data types. MySQL is simpler to set up, has wider hosting support, and may be preferable for read-heavy workloads with simple queries. PostgreSQL excels at data integrity, complex relationships, and extensibility. MySQL excels at raw read speed for simple queries and has broader legacy hosting support. Both are production-grade, open-source, and free.
We use PostgreSQL for every project at Hunchbite. We're biased — and we'll be upfront about that. But we'll also tell you the specific situations where MySQL is the better choice, because they exist.
The database decision is one of the hardest to reverse. Switching databases after you've built an application on one is expensive, risky, and painful. This guide helps you make the right call before you start writing code.
| Factor | PostgreSQL | MySQL |
|---|---|---|
| License | PostgreSQL License (fully open) | GPL v2 (with Oracle ownership caveats) |
| SQL compliance | Very high | Moderate (improving) |
| JSON support | Excellent (JSONB — indexed, queryable) | Basic (JSON type, limited indexing) |
| Full-text search | Built-in (tsvector, tsquery) | Built-in (simpler, less flexible) |
| GIS/Geospatial | PostGIS (industry standard) | Basic spatial support |
| Concurrent writes | MVCC — excellent | Good (InnoDB), can lock under heavy writes |
| Read performance (simple) | Very fast | Slightly faster for simple SELECT |
| Complex queries | Excellent optimizer | Adequate, weaker on complex JOINs |
| Replication | Logical + physical | Built-in, mature |
| Extensions | Rich (PostGIS, pg_trgm, hstore, vector) | Limited (plugins, not extensions) |
| Hosting support | Major clouds, Supabase, Neon | Everywhere — including shared hosting |
| Community | Growing fast | Massive, mature |
| Default character set | UTF-8 | Historically latin1 (now utf8mb4) |
PostgreSQL's query optimizer handles complex JOINs, subqueries, and CTEs (Common Table Expressions) significantly better than MySQL. If your application has deeply relational data — users with roles with permissions with organizations with billing — PostgreSQL's optimizer will produce better query plans as complexity grows.
This matters more than benchmarks suggest. The difference between a good and bad query plan on a complex JOIN across 5 tables with millions of rows isn't 10% — it can be 10×.
PostgreSQL's JSONB data type is genuinely powerful. You can store JSON, index specific keys within it, query nested fields, and combine JSON operations with relational queries in a single statement.
This means you can have the relational model for your core data (users, orders, products) and flexible JSON fields for data that doesn't fit a rigid schema (user preferences, product metadata, event payloads) — all in one database.
MySQL has a JSON type, but it's significantly less capable. You can't efficiently index JSON fields, and the query syntax for JSON operations is more limited.
PostgreSQL's built-in full-text search (tsvector, tsquery) supports stemming, ranking, phrase matching, and accent-insensitive search. For many applications, it's good enough to replace a dedicated search engine like Elasticsearch.
We've shipped product search, documentation search, and content search features using PostgreSQL full-text search alone — saving clients the operational complexity of a separate search service.
PostGIS is the industry standard for geospatial data. If your application involves location data — store locators, delivery zones, geographic analysis, mapping — PostgreSQL with PostGIS is the default choice. Nothing else comes close.
PostgreSQL is stricter by default. It won't silently truncate data, convert invalid dates to zeroes, or accept values that violate constraints. MySQL historically had permissive defaults that could corrupt data silently (though strict mode, now default, has largely fixed this).
For financial applications, healthcare systems, or any domain where data accuracy is critical, PostgreSQL's strictness is a feature.
PostgreSQL's extension system is uniquely powerful. You can add:
This extensibility means PostgreSQL can handle specialized workloads that would otherwise require separate services.
MySQL with InnoDB is exceptionally fast for simple SELECT queries on well-indexed tables. If your application is 90% reads, the queries are straightforward (SELECT with simple WHERE clauses, no complex JOINs), and the data model is simple — MySQL is slightly faster and uses fewer resources.
Blog platforms, content management systems, and simple CRUD applications with high read-to-write ratios fall into this category.
If you're running WordPress, WooCommerce, Magento, Drupal, or most PHP frameworks — MySQL is the default. The entire PHP ecosystem is built around MySQL. Fighting this default adds complexity for no benefit.
We wouldn't recommend migrating a WordPress site's database to PostgreSQL. Use the right tool for the ecosystem.
MySQL runs on practically every hosting environment, including $5/month shared hosting. PostgreSQL support is now widespread on major cloud providers but is less common on budget hosting and legacy infrastructure.
If deployment constraints limit your hosting options, MySQL's ubiquity is a genuine advantage.
If your team has deep MySQL expertise and limited PostgreSQL experience, the migration cost (in learning curve, in mistakes, in slower development) needs to justify the switch. For straightforward applications, MySQL expertise beats PostgreSQL's technical advantages.
Most "PostgreSQL vs MySQL performance" articles are misleading because they benchmark simple queries in isolation. Real-world performance depends on:
Where PostgreSQL typically wins:
Where MySQL typically wins:
Where neither wins:
For most web applications, the performance difference between PostgreSQL and MySQL is immeasurable in production. Your ORM, your query design, your indexing strategy, and your caching layer matter 100× more than the database engine.
Both databases have excellent managed hosting in 2026:
PostgreSQL:
MySQL:
The hosting story has converged. Both databases are available as managed services from every major cloud provider. The "MySQL has better hosting" argument is largely a relic of the shared hosting era.
Migrating from MySQL to PostgreSQL (or vice versa) is harder than it should be.
Schema differences: Data types don't map 1:1. MySQL's TINYINT(1) for booleans becomes BOOLEAN in PostgreSQL. AUTO_INCREMENT becomes SERIAL or GENERATED ALWAYS AS IDENTITY. ENUM types work differently. DATETIME vs TIMESTAMP semantics differ.
Query differences: MySQL uses backticks for identifiers, PostgreSQL uses double quotes. LIMIT syntax differs slightly. Group-by behavior differs (PostgreSQL is stricter and more correct). MySQL-specific functions don't exist in PostgreSQL.
ORM mitigation: If you use an ORM (Prisma, Drizzle, TypeORM, Sequelize), the ORM abstracts most of these differences. Migrating an ORM-based application between databases is significantly easier than migrating raw SQL applications.
Our advice: choose correctly upfront. Database migration mid-project is costly and risky, even with an ORM. The time you spend evaluating now saves multiples later.
Default to PostgreSQL for new projects. The combination of JSONB, full-text search, PostGIS, extensions (especially pgvector for AI features), and strict data integrity makes it the more capable database for the widest range of applications.
Choose MySQL when you're working within a PHP/WordPress ecosystem, your team has deep MySQL expertise, or your workload is predominantly simple reads on simple schemas.
Don't migrate from MySQL to PostgreSQL unless you have a specific technical need that MySQL can't meet. "PostgreSQL is better" isn't a sufficient justification for the cost and risk of database migration.
For our projects, we pair PostgreSQL with Prisma or Drizzle as the ORM, and deploy on either Supabase or Neon depending on the project's needs. This stack handles everything from simple CRUD applications to complex SaaS platforms with real-time features.
To see how PostgreSQL fits into our full technology stack, or to learn more about our API development services, check those pages out. If you're evaluating backend-as-a-service options, our comparison of Supabase vs Firebase covers the managed database layer in detail.
Need help choosing the right database — or migrating from one to another? Get started with a conversation. We'll look at your data model, query patterns, and scale requirements and give you an honest recommendation.
If this guide resonated with your situation, let's talk. We offer a free 30-minute discovery call — no pitch, just honest advice on your specific project.
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