Postgres vs MySQL in 2026 - Differences That Matter for Apps

For a new app in 2026, Postgres is the default choice for most teams: it has richer types, transactional schema changes, row level security, and an extension ecosystem (pgvector, PostGIS, pg_cron) that MySQL doesn't match. MySQL is still an excellent database, simpler to operate at very large scale in some setups, and the right pick when your stack, team or host is built around it. Both are fast enough for nearly any app; the differences are in features and ecosystem, not raw speed.

Below are the differences you'll actually run into while building an app, with SQL for each.

#Quick comparison

Version facts from PostgreSQL's versioning policy and MySQL's release model. PostgreSQL 14 reaches end of life on November 12, 2026, so plan upgrades if you're on it.

#Data types

Postgres has more types out of the box, and they save application code: uuid, timestamptz, arrays, ranges, inet, interval, enums and composite types.

-- Postgres: an array of tags and a time range, both indexable
create table events (
  id uuid primary key default gen_random_uuid(),
  tags text[] not null default '{}',
  during tstzrange not null
);
create index on events using gin (tags);
select * from events where tags @> array['launch'];

In MySQL you'd model tags as a join table or a JSON array, and the time range as two columns. That's fine, just more code.

#JSON

Both store JSON. Postgres's jsonb is stored in a binary format and can be indexed as a whole with GIN:

create index on products using gin (attributes jsonb_path_ops);
select * from products where attributes @> '{"color": "red"}';

MySQL indexes JSON by extracting values into generated columns or with multi-valued indexes for arrays. It works well when you know which keys you'll query; Postgres is more flexible when you don't.

#Transactions and schema changes

Postgres runs DDL inside transactions. A migration that adds a column, backfills it and adds a constraint either fully succeeds or fully rolls back:

begin;
alter table orders add column currency text;
update orders set currency = 'EUR' where currency is null;
alter table orders alter column currency set not null;
commit;

In MySQL, most DDL statements commit implicitly, so a failure halfway leaves a partial migration you clean up by hand. Migration tools work around it, but the safety net is different.

Isolation defaults also differ. Postgres defaults to READ COMMITTED; MySQL's InnoDB to REPEATABLE READ. Both support SERIALIZABLE. If you port code, check the assumptions your transactions make.

#Security inside the database

Postgres has row level security: policies that filter rows per user, enforced by the database for every query.

alter table documents enable row level security;
create policy "Owners only" on documents
  for all using (owner_id = current_setting('app.user_id')::uuid);

This is why Postgres-based backends (Supabase, StitchDB) can let browsers and mobile apps query the database through an API safely: the policy runs no matter which client sends the query, using auth.uid() from the user's token. MySQL has no built-in equivalent; you enforce access in application code or with views per user.

#Extensions

Postgres extensions add whole capabilities without another service:

• pgvector for embeddings and semantic search
• PostGIS for geospatial queries
• pg_cron for scheduled jobs (cron docs)
• pg_trgm for fuzzy text search
• pg_stat_statements for query statistics

create extension if not exists vector with schema extensions;
create table docs (id bigint primary key, embedding vector(1536));
select id from docs order by embedding <=> '[0.01, ...]' limit 5;

MySQL has plugins and its own spatial and full-text features, but no ecosystem of this size. For AI features in particular, pgvector inside your main database is a big simplification.

#Performance

Benchmarks go both ways depending on workload, configuration and version, so be skeptical of general claims. Some structural differences that matter in practice:

• MySQL InnoDB stores rows in primary key order (a clustered index). Lookups by primary key are very efficient; random UUID primary keys cause page splits. Prefer ordered keys.
• Postgres uses MVCC with VACUUM. Updates create new row versions and autovacuum cleans up. Heavy-update tables need attention to vacuum settings.
• Connections: Postgres uses a process per connection, so use a pooler for many clients (for example StitchDB pooling on ports 5432 and 6543); see connection pooling explained.

For a typical web or mobile app, either database will be faster than your network round-trips. Index the queries you run and both perform well.

#Replication and scaling

Both have mature primary-replica replication. MySQL has a long history of very large sharded deployments, and Vitess (behind PlanetScale's MySQL product) shards MySQL horizontally. Postgres scales vertically very far, offers read replicas, logical replication and partitioning, and sharding through extensions or platforms.

If you expect to need horizontal sharding from day one, MySQL with Vitess is a proven path. Most apps never get there.

#Hosting options

Both are available from every major cloud. Some notes as of November 2026:

• PlanetScale offers both Postgres (from $5/month for a single PS-5 node) and Vitess/MySQL (from $39/month for a three-node cluster), per its pricing page.
• Postgres-based backends add an API, auth and storage on top. StitchDB gives each project a dedicated Postgres database with an auto-generated REST and GraphQL API, Auth and Storage; plans start free, and Pro is $15.99/month (pricing). It's EU-hosted only.

If you're moving from MySQL, see Migrate from PlanetScale (MySQL) to Postgres.

#Upsert and returning rows

Small syntax differences show up in everyday code. Postgres inserts or updates with on conflict and can return the written rows in the same statement:

insert into stock (sku, qty) values ('A-1', 5)
on conflict (sku) do update set qty = stock.qty + excluded.qty
returning sku, qty;

MySQL uses insert ... on duplicate key update for the same idea. returning saves a second query in APIs that need to send back the saved row, which is why REST layers built on Postgres return the created record directly.

#Which should you pick?

Pick Postgres if:

• you're starting a new app and have no strong reason otherwise
• you want row level security, JSON flexibility, or extensions like pgvector
• you want a backend-as-a-service on top of your database

Pick MySQL if:

• your team, framework or host is built around it (for example, an existing PHP stack)
• you plan horizontal sharding with Vitess
• you're extending an existing MySQL system

#FAQ

#Is Postgres faster than MySQL?

Neither is faster in general. It depends on the workload, schema and configuration. For most apps, indexing and query design matter far more than the engine.

#Is Postgres harder to learn than MySQL?

Basic SQL is nearly identical. Postgres has more features to learn, but you don't need them on day one.

#Can I switch from MySQL to Postgres later?

Yes, with tools like pgloader, but types, functions and some SQL syntax need translating. It's easier early.

#Which do backend as a service platforms use?

Most SQL-based BaaS platforms (Supabase, StitchDB, Nhost) use Postgres, mainly for row level security.

Start a new app on Postgres with the API already built: create a free StitchDB project.