PostgreSQL vs MySQL
I use PostgreSQL for everything. I've used MySQL on older projects. Both work, but for a new SaaS in 2026, PostgreSQL is the stronger choice.
Quick Comparison
| PostgreSQL | MySQL | |
|---|---|---|
| License | PostgreSQL License (permissive) | GPL v2 (with commercial option) |
| Owned by | Community-governed | Oracle |
| JSONB support | Native, indexed, queryable | JSON type (less capable) |
| Full-text search | Built-in | Built-in (different approach) |
| Extensions | Rich ecosystem (PostGIS, pgvector, etc.) | Limited plugin system |
| SQL compliance | High | Moderate (improving) |
| TypeScript ORMs | Drizzle, Prisma, Kysely, TypeORM | Drizzle, Prisma, Kysely, TypeORM |
| Default in | Supabase, Render, Railway | PlanetScale, many legacy apps |
Data Integrity
PostgreSQL is stricter by default. It enforces constraints, rejects invalid data types, and follows SQL standards closely. MySQL was historically more lenient — accepting truncated data, allowing invalid dates, silently converting types.
MySQL has improved with strict mode (enabled by default since 5.7), but PostgreSQL's defaults are still more protective. For a SaaS where data correctness matters — billing records, user permissions, subscription states — I want the database catching my mistakes, not silently swallowing them.
JSONB
PostgreSQL's JSONB is genuinely useful. Store JSON, index it with GIN indexes, query nested fields efficiently. You get document-database flexibility without leaving your relational database.
MySQL has a JSON type, but indexing JSON fields requires generated columns, and query performance on large JSON datasets doesn't match PostgreSQL's JSONB.
I use JSONB for user preferences, webhook payloads, and API responses. No need for a separate document store.
Performance
For typical SaaS workloads — CRUD operations, joins across a handful of tables, some aggregations — both perform well. You won't notice a difference for most applications.
Where they diverge:
- Simple read-heavy workloads: MySQL can be slightly faster for basic SELECTs
- Complex queries: PostgreSQL's query planner handles joins, subqueries, and CTEs better
- Write-heavy with constraints: PostgreSQL handles concurrent writes more gracefully
- Full-text search: PostgreSQL's built-in search is more capable without external tools
In practice, your query design and indexing strategy matter far more than which database you pick.
Extensions
PostgreSQL's extension system is a real advantage. PostGIS for geospatial data, pgvector for AI embeddings, pg_cron for scheduled jobs. These run inside the database with native performance.
MySQL's plugin system is more limited. For geospatial work, vector search, or anything beyond basics, you'll often need external services.
If your SaaS might need vector search for AI features — and that's getting common — pgvector means you can add it without spinning up a separate service.
TypeScript Integration
Both work well with modern TypeScript ORMs. Drizzle, Prisma, and Kysely support both.
One difference: PostgreSQL supports more types natively — arrays, enums, JSONB, composite types. That translates to richer type definitions in your ORM. With MySQL, you'll use JSON strings or junction tables where PostgreSQL uses native arrays.
Drizzle in particular has strong PostgreSQL support, using RETURNING clauses, native enums, and JSONB operations.
Migrations
PostgreSQL supports transactional DDL — schema changes run inside transactions and can be rolled back atomically. MySQL doesn't for most DDL operations. If a migration fails halfway with MySQL, you might end up with a partially applied state.
For production SaaS deployments, transactional DDL is a meaningful safety net.
When to Choose PostgreSQL
- You want the most capable open-source database
- You need JSONB for semi-structured data
- You value strict data integrity defaults
- You might need extensions (geospatial, vector search, cron)
- You want transactional DDL for safer migrations
- You're building with modern TypeScript tooling
When to Choose MySQL
- Your team has deep MySQL expertise
- You're working with existing MySQL infrastructure
- You need MySQL-specific compatibility (PlanetScale, legacy systems)
- You're migrating from a MySQL-based system
What Stacknaut Uses
I chose PostgreSQL with Drizzle ORM.
If you've decided on PostgreSQL, the next step is wiring up the ORM, writing schema definitions, setting up migrations, configuring connection pooling, and making sure types flow cleanly between your database, backend, and frontend. That's a few hours of plumbing before you can build anything.
Stacknaut includes all of it — schema definitions in TypeScript, Drizzle Kit migrations, type-safe queries, and a shared package that exports database types used by both backend and frontend. You define your tables, run migrations, and start building. The plumbing is done.
See what's included or check out the full-stack TypeScript architecture.