Fazlur Rahman
PostgreSQL vs MySQL is a real choice in 2026, and the right pick depends on the workload. PostgreSQL is the better pick for complex queries, JSON data, full-text search, and analytical workloads. MySQL is the better pick for simple CRUD, high-read web apps, and managed cloud scaling.
Where each database leads
PostgreSQL is the better pick for complex queries with joins, subqueries, and aggregations. The query planner is the most mature in the open-source database world, the indexing options are the most flexible, and the SQL/JSON support is the best. PostgreSQL is also the better pick for analytical workloads, with window functions, common table expressions, and the ability to handle very large result sets without breaking a sweat.
MySQL is the better pick for simple read-heavy web apps. The InnoDB storage engine is fast, the replication is straightforward, and the managed cloud services (Aurora, PlanetScale, Vitess) are the most mature. MySQL is also the right pick when the team is familiar with it and the workload is CRUD.
Performance
For simple read-heavy workloads, MySQL is faster than PostgreSQL. The InnoDB storage engine is optimized for the read path, and the query execution is simpler. For complex queries with joins, subqueries, and aggregations, PostgreSQL is faster than MySQL. The query planner makes better decisions on the complex queries, and the indexing is more flexible.
The performance difference is small for typical web app workloads. The right pick is the one that matches the application requirements, not the one with the highest benchmark score.
JSON and document data
PostgreSQL is the better pick for JSON data in 2026. The JSONB type, the rich indexing on JSONB fields, and the SQL/JSON path expressions are the best in any open-source database. The right call is to use JSONB in PostgreSQL for any application that stores JSON documents alongside relational data.
MySQL has JSON support but is less mature. The indexing on JSON fields is less flexible, and the query path is more rigid. The right call is to use MySQL for JSON only if the team is already on MySQL and the JSON usage is simple.
Full-text search
PostgreSQL is the better pick for full-text search in 2026. The tsvector type, the rich set of text search functions, and the ability to combine text search with relational queries are the best in any open-source database. The right call is to use PostgreSQL for any application with significant text search requirements.
MySQL has full-text search but is less mature. The functionality is improving with each release, but the query path is less flexible.
Replication and scaling
MySQL has the most mature replication story. The MySQL replication is straightforward, the read replicas are well-tested, and the managed cloud services (Aurora, PlanetScale) handle horizontal scaling well. PostgreSQL replication is more flexible but is less polished, especially for very large databases.
For very large databases, both databases need sharding or partitioning. MySQL with Vitess is the most mature sharding solution. PostgreSQL with Citus is a strong alternative for analytical workloads.
Managed cloud services
Both AWS RDS and Aurora support MySQL and PostgreSQL with managed backups, patching, and failover. Aurora MySQL is the faster choice for simple read-heavy workloads, and Aurora PostgreSQL is the faster choice for complex queries. Google Cloud SQL and Azure Database are similar.
The right call is the same as the underlying database: MySQL for simple CRUD, PostgreSQL for complex queries and JSON. The managed service tier is roughly the same price for both.
Migration between the two
Migrating from MySQL to PostgreSQL is supported by tools like pgLoader and AWS DMS. The most common migration is from MySQL to PostgreSQL when the application grows from simple CRUD to complex queries. The migration typically takes a few days for a small app and a few weeks for a large one.
Migrating from PostgreSQL to MySQL is less common and is harder, especially if the application uses JSONB heavily. The right call is to migrate from PostgreSQL to MySQL only if the team is more familiar with MySQL and the application does not use the PostgreSQL-specific features.
Common mistakes to avoid
The most common mistake is to pick a database based on the headline benchmark without testing it on the actual workload. The right call is to take a small but representative sample of the actual queries and run them through each database. The 10 hour test is usually enough to know which database is the right fit.
The second most common mistake is to migrate between databases without planning. The migration is the right call for a workload change, but the right call is to plan the migration carefully, with a fallback to the old database. The migration is a real project, not a weekend hack.
The third most common mistake is to over-rely on the database features that are not portable. The right call is to use the standard SQL features that are available in both databases, and to use the database-specific features only when the migration is unlikely.
The honest short version
PostgreSQL is the better pick for complex queries, JSON data, full-text search, and analytical workloads. MySQL is the better pick for simple CRUD, high-read web apps, and managed cloud scaling. The two are close on most tasks, so the right pick depends on the workload and the team familiarity.
Photo: Two Micron All-Sky Survey, Public Domain (NASA), via NASA Image and Video Library (https://images.nasa.gov/details/PIA04251)
