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Head-to-head · Relational databases

Postgres vs MySQL

Postgres vs MySQL in 2026: features, performance, JSON support, replication, ecosystem. Pick by feature needs and hosting platform.

Updated May 2026 · 7 min read
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Postgres and MySQL both run a huge fraction of the production internet. Postgres has won the new-greenfield market over the last decade — better feature set, stricter SQL, JSON-as-a-document-store. MySQL still wins on legacy momentum, raw single-node read throughput, and a few hosting setups. Pick by what features you actually need, not by what's cooler.

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Option 1

Postgres

Feature-rich; default for new projects; pgvector for AI.

Best for

Greenfield apps, anything that needs JSON-as-document, RAG / vector search, complex analytical queries, strict ACID + advanced indexing.

Pros

  • Best-in-class feature set: JSON/JSONB indexing, full-text search, generated columns, partial indexes, materialized views
  • Standards-compliant SQL — fewer 'this only works in MySQL' surprises
  • pgvector for AI/RAG (embeddings + vector similarity search) is the standard
  • Excellent extension ecosystem (PostGIS for geospatial, pg_cron for scheduling, Citus for distribution)
  • Streaming replication + logical replication both first-class
  • Available on every cloud (RDS, Supabase, Neon, Crunchy, Railway)

Cons

  • Heavier than MySQL on small VMs (more memory baseline)
  • Connection scaling needs a pooler (PgBouncer) past ~100 connections
  • Vacuum + bloat behavior takes ops awareness on big workloads

Option 2

MySQL / MariaDB

Legacy momentum; simpler ops; PlanetScale.

Best for

Existing MySQL stacks, WordPress / Drupal installations, simple read-heavy workloads, teams using PlanetScale or Vitess.

Pros

  • Simpler ops out of the box: replication setup is easier
  • Higher peak read throughput on single-node OLTP for simple queries
  • PlanetScale (built on Vitess) gives serverless scaling + branching
  • MariaDB fork is a fully drop-in alternative if you want non-Oracle stewardship
  • PHP / WordPress / Drupal ecosystem assumes MySQL
  • Smaller memory footprint on tight VMs

Cons

  • Weaker JSON / full-text features than Postgres (improving slowly)
  • Oracle stewardship of MySQL proper has slowed feature pace; MariaDB is the active fork
  • No first-class vector / pgvector equivalent for AI workloads
  • Default character set / collation gotchas (utf8 vs utf8mb4 historically)

The verdict

New project, no constraint → Postgres; the feature set + ecosystem + AI primitives win. Existing stack on MySQL with a working setup → don't migrate without reason; both are production-grade. WordPress / Drupal / legacy LAMP → MySQL or MariaDB, the ecosystem assumes it. SQLite at small scale + Postgres at growth scale is a common pattern; Turso (libSQL) extends that to multi-region SQLite.

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Guides on this topic

Deeper reads that go beyond the head-to-head — primary-source data, edge cases, and the questions you’ll have after you’ve picked a side.

Frequently asked questions

Can I migrate MySQL → Postgres?

Doable but real work. Schema differences (auto_increment vs SERIAL, JSON column behavior, GROUP BY rules), tooling differences (mysqldump → pg_dump translation, ORMs that emit MySQL-specific SQL). Plan multi-week effort for non-trivial apps.

What about CockroachDB / TiDB / Yugabyte?

Distributed SQL options. They speak Postgres or MySQL wire protocol but offer global ACID + horizontal scaling. Worth evaluating at scale; for typical apps a managed Postgres on Neon or Supabase covers it cheaper.

Postgres for new projects always?

If unsure, Postgres. The exception is when you're hard-pinned to a MySQL ecosystem (PlanetScale's branching workflow, WordPress, etc.) where MySQL's tooling has a clear advantage.

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