01 · Section
Postgres wins on feature surface
JSONB with proper indexing, full-text search, materialised views, partial indexes, generated columns, real ENUM types, native UUIDs, robust extensions (PostGIS, pgvector, TimescaleDB). For any product whose data model will evolve or include search, analytics or geo, Postgres is the safer default.
pgvector specifically has made Postgres the de facto choice for AI/RAG workloads — your operational database and your vector store can be the same system, which is one less moving part.
02 · Section
MySQL still wins on operational simplicity
MySQL 8 with InnoDB is rock solid, replication is well understood, and managed offerings (RDS, Aurora, PlanetScale) are extremely mature. For high write throughput on simple schemas — think Shopify-shaped workloads — MySQL/Vitess scales further with less ceremony.
If your team has deep MySQL ops experience and your data model is flat and well-defined, switching to Postgres for novelty is not worth it.
03 · Section
A decision framework
Will the schema evolve significantly? → Postgres.
Will you do search, vector, geo or analytics on the same DB? → Postgres.
Is your write throughput already the bottleneck and is the schema simple? → MySQL/Vitess.
Does your team know one of them deeply? → Stick with it.
For most new SaaS products in 2026, the default is Postgres. The exceptions are real but specific.
Key takeaways
- Default to Postgres for new SaaS unless you have a specific reason not to.
- pgvector lets you keep operational and vector data in one system.
- MySQL/Vitess still wins for very high write throughput on simple schemas.
- Team expertise outweighs theoretical advantages — pick what you can operate.
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Written by
Hassan Ali
7 min read · Posted in Cloud Computing