Postgres vs MySQL in 2026 — Which Database Should You Choose?

This comparison gets written every year. In 2026, with Postgres 17 and MySQL 9.x, here's where the line actually falls.

Where Postgres Clearly Wins

JSON/JSONB

Postgres JSONB is indexed, queryable, and has a rich operator set:

SELECT * FROM users WHERE preferences @> '{"theme": "dark"}';
CREATE INDEX idx_user_prefs ON users USING gin(preferences);

Full-Text Search

Postgres ships a capable built-in FTS engine — enough to skip Elasticsearch for most apps:

SELECT * FROM articles
WHERE to_tsvector('english', title || ' ' || body)
    @@ plainto_tsquery('english', 'server components');

Advanced Data Types

Arrays, ranges, composite types — fewer application-layer workarounds:

ALTER TABLE articles ADD COLUMN tags text[];
SELECT * FROM articles WHERE 'typescript' = ANY(tags);

Extension Ecosystem

pgvector for AI similarity search, PostGIS for geospatial, timescaledb for time-series. MySQL has no equivalent ecosystem.

Where MySQL Holds Its Ground

Replication maturity — 20 years of battle-tested primary-replica tooling (Percona, ProxySQL).

Managed cost — AWS Aurora MySQL and Cloud SQL MySQL are cheaper than Postgres equivalents at scale.

Read routing — ProxySQL and Vitess for sophisticated read/write splitting are more mature on MySQL.

Team expertise — if your team knows MySQL deeply, that knowledge is operationally valuable.

The Decision Guide

Either works fine for: standard CRUD APIs, relational data with foreign keys, most startups under 10M rows per table.

My Default

For new projects with no specific constraints: Postgres. More expressive, unmatched extension ecosystem, and Supabase/Neon make it as easy to operate as any database has ever been.

But I'd never tell a team to migrate away from a well-functioning MySQL setup. The grass isn't that much greener.