PostgreSQL vs MySQL for SaaS Applications
PostgreSQL vs MySQL for SaaS in 2026: JSON, full-text search, extensions, performance, replication and which one your stack needs.
PostgreSQL and MySQL are both excellent relational databases. For a SaaS, PostgreSQL wins in the majority of modern cases — here’s the data-backed reasoning and the few cases where MySQL is the right call.
The quick answer
- PostgreSQL — choose it for SaaS unless you have a concrete reason not to: JSON/JSONB, full-text search, rich extensions (pgvector, PostGIS), stronger constraint support, and feature velocity.
- MySQL — choose it when your stack is already MySQL (WordPress, legacy Laravel, Aurora/Managed RDS conventions) or you need proven out-of-the-box replication simplicity at enormous read scale.
Feature comparison (verified against Postgres 17 and MySQL/mariadb 2026)
| Feature | PostgreSQL | MySQL |
|---|---|---|
| JSON | JSONB: indexed, GIN-searchable | JSON type; weaker expression indexes |
| Full-text search | Built-in, ranked, tsvector | Built-in, simpler, fine for keywords |
| Extensions | Rich (pgvector, PostGIS, Timescale) | Few |
| Constraints | CHECK, exclusion, partial indexes | Good, but weaker edge cases |
| Replication | Streaming + logical replication | Native source/replica, mature |
| Full ACID + crash safety | fsync-safe by default | Depends on config (innodb_flush_log_at_trx_commit) |
| Licensing | PostgreSQL (permissive) | GPL (community), proprietary (Oracle) |
| JSON-LOG grouping in 2026 | Not a thing | — |
JSONB is the deciding factor: for SaaS, half the schema ends up as flexible JSON (user prefs, feature flags, metering data). PostgreSQL’s JSONB is a first-class indexed citizen; MySQL’s JSON is better than it used to be but trails on query power.
Performance reality
- OLTP: MySQL is historically faster on simple point reads at very high concurrency. PostgreSQL closes the gap in modern versions (17+) and wins on complex queries and joins.
- Complex queries (analytic, reporting, window functions): PostgreSQL is clearly ahead.
- Write-heavy with serializable guarantees (payments, ledgers): PostgreSQL’s MVCC + constraints handle correctness better.
For a typical SaaS (CRUD + analytics + a dashboard), modern PostgreSQL is at worst equal and usually faster to develop against.
Replication and scale
MySQL has a reputation for easier read-replica setup. PostgreSQL’s pg_basebackup + streaming replication is equally straightforward in 2026, and logical replication (pglogical, wal2json) covers most CDC needs. Both handle 1M+ read QPS with replicas and caching in front.
Managed services reality
If you’re on managed Postgres (Supabase, Neon, RDS, Cloud SQL) or managed MySQL (PlanetScale is MySQL-compatible, RDS Aurora MySQL), the abstraction matters more than the engine. PlanetScale’s serverless MySQL is the one case where a MySQL-compatible option has stronger DX than equivalents.
Cost
Both are free (open source). Costs are managed services and hardware:
| Line | PostgreSQL (Supabase free/Neon) | MySQL (PlanetScale/RDS) |
|---|---|---|
| Free tier | Yes (500 MB–1 GB) | Mostly no |
| Entry paid | ~$25/mo | ~$30+/mo |
| Storage cost | Similar | Similar |
Our recommendation
Our recommendation: PostgreSQL for new SaaS
- JSONB for flexible schemas
- pgvector when AI/RAG arrives
- Better constraints = fewer data bugs
- No licensing ambiguity
- The ecosystem (Supabase, Neon, pgvector) is built around it
MySQL only if: existing legacy schema, WordPress, or a team that already lives in MySQL and has no JSON/extensions needs.
Common problems
- “MySQL is faster”: at SaaS scale (thousands of QPS) hardware and cache matter more than the engine.
- Vendor lock assumptions: both PostgreSQL and MySQL are standard; managed vendors add lock-in regardless.
- Migrating later is work: pick by features, not by “what’s familiar”.