PostgreSQL vs MySQL

PostgreSQL and MySQL are the two most widely used open-source relational databases, and comparisons between them come up constantly when teams choose a database for a new project. Both are mature, battle-tested, and used at massive scale in production — this is not a case of one being “good” and the other “bad.” The differences are mostly about depth of features, strictness, and the kinds of workloads each was historically tuned for.

Side-by-side comparison

Aspect	PostgreSQL	MySQL
Standards compliance	Very close adherence to the SQL standard	Historically more relaxed; has improved significantly in recent versions
Data types	Rich: JSONB, arrays, ranges, composite types, custom types	More limited built-in set; JSON support added later and less deeply integrated
Concurrency model	MVCC (Multi-Version Concurrency Control), built into the core	MVCC via the InnoDB storage engine (the default engine)
Extensibility	Extensions, custom types, custom operators, custom index types	More limited extension mechanisms
Full-text & JSON search	Native full-text search plus indexable JSONB	Full-text search available; JSON support is functional but less feature-rich
Licensing	PostgreSQL License (permissive)	GPL, with a commercial dual-license offered by Oracle
Typical strengths	Complex queries, analytics, data integrity, advanced data modeling	Simple, read-heavy web applications; historically very fast for basic CRUD

Concurrency: MVCC in both, implemented differently

Both databases use MVCC to let readers and writers work concurrently without blocking each other for most operations. The difference is in the details: PostgreSQL implements MVCC at the core storage level for every table, while in MySQL it depends on the storage engine — MVCC applies when using InnoDB (the default and recommended engine today), but not with older engines like MyISAM. In practice, almost all modern MySQL deployments use InnoDB, so this gap matters less than it used to.

Data types: where PostgreSQL pulls ahead

This is usually the biggest practical difference. PostgreSQL’s JSONB type stores JSON in an efficient binary format that can be indexed and queried with operators, which makes Postgres a genuinely good fit for semi-structured data without giving up SQL:

Querying inside a JSONB column

SQL

SELECT name
FROM products
WHERE attributes @> '{"color": "red"}';

PostgreSQL also has native array columns, range types (for dates, numbers, and timestamps), and the ability to define your own composite and enumerated types. MySQL has been adding JSON functions over the years, but the depth of native support and indexing options still favors PostgreSQL for anything beyond simple key lookups.

When to reach for which

Choose PostgreSQL when your application needs complex queries, strong data integrity guarantees, advanced data types (JSONB, arrays, ranges), geospatial data (PostGIS), or heavy analytical workloads
Choose MySQL when you want a database with an enormous hosting ecosystem, extremely simple setup, and your workload is largely straightforward reads/writes without complex relational logic
Either works well for typical CRUD-style web applications — the choice often comes down to team familiarity, hosting/ecosystem constraints, or existing infrastructure

The gap has narrowed

MySQL has closed a lot of ground in recent major versions — window functions, common table expressions (CTEs), and better JSON support all arrived in MySQL 8.0. Meanwhile PostgreSQL has kept pushing further ahead on advanced features. For basic applications, both are excellent, well-supported choices; the differences described here matter most once you need the advanced capabilities.