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PostgreSQL vs MySQL: Which Database Should You Use?

PostgreSQL and MySQL are the two most widely used open-source relational databases, and both run some of the largest applications in the world. MySQL, now owned by Oracle, became popular as the M in the LAMP stack and powers WordPress and many PHP applications. PostgreSQL, developed by a global community, has a reputation for standards compliance, extensibility and advanced features.

Quick verdict

PostgreSQL and MySQL are both mature, open-source relational databases. PostgreSQL offers richer SQL, advanced data types, JSONB, powerful indexing and extensions such as PostGIS and pgvector, suiting complex and analytical workloads. MySQL is simpler to operate, very fast for read-heavy web traffic and supported everywhere. Choose PostgreSQL for feature depth and complex queries, MySQL for straightforward, high-read web applications.

The gap has narrowed over time. MySQL 8 added window functions, common table expressions and better JSON support, while PostgreSQL has improved replication and performance. Today the choice usually depends on your feature needs, your team's experience, your hosting platform and how the database must scale.

PostgreSQL vs MySQL, side by side

CriterionPostgreSQLMySQL
LicensePostgreSQL License, a permissive open-source licenseGPL community edition; commercial licenses from Oracle
SQL featuresVery rich: CTEs, window functions, partial and expression indexesSolid core SQL; window functions and CTEs since version 8
JSONJSONB with GIN indexing and powerful operatorsJSON type with functional and multi-valued indexes
Data typesArrays, ranges, enums, network types, custom typesStandard types plus spatial and JSON
ExtensionsPostGIS, pgvector, TimescaleDB, Citus and many moreLimited extension model; uses storage engines instead
ConcurrencyMVCC; process per connection, so pooling with PgBouncer is commonInnoDB MVCC; thread per connection handles many connections
Read-heavy performanceFast; excels at complex queriesVery fast for simple reads and primary-key lookups
Replication and scalingStreaming and logical replication; Citus for shardingMature replication, Group Replication, Vitess for sharding
Managed optionsRDS, Aurora, Cloud SQL, Azure, Supabase, NeonRDS, Aurora, Cloud SQL, Azure, PlanetScale
Best fitComplex apps, analytics, geospatial, AI search, SaaSCMS, ecommerce, read-heavy web apps, PHP stacks

Choose PostgreSQL when

  • You need complex queries, reporting or analytics on the same database as your application.
  • You want geospatial features with PostGIS or vector similarity search with pgvector.
  • Your data model uses JSON documents alongside relational tables and you need to index them well.
  • You value strict data integrity, rich constraints and standards-compliant SQL.
  • You are building a multi-tenant SaaS product that may need advanced partitioning or row-level security.

Choose MySQL when

  • You are running WordPress, Magento or another platform built primarily for MySQL.
  • The workload is read-heavy with simple queries, such as content sites and catalogs.
  • Your team and hosting provider have deep MySQL operational experience.
  • You plan to shard horizontally with Vitess or a platform built on it.
  • You need very wide compatibility with low-cost shared hosting.

Features that usually tip the decision

PostgreSQL's extension system is its biggest differentiator. PostGIS makes it a leading geospatial database, pgvector adds embedding storage and similarity search for AI features, and TimescaleDB adds time-series capabilities, all inside one database with normal SQL. Features like partial indexes, row-level security and transactional schema changes also help complex, multi-tenant applications.

MySQL's strength is operational simplicity at scale for common web workloads. Replication is well understood, hosting support is universal and many developers know it from PHP projects. Very large MySQL deployments use Vitess to shard transparently. MariaDB, a community fork, is another option with high compatibility for most applications.

Performance and operations

Benchmarks rarely settle this debate, because results depend on schema, indexes, configuration and query patterns. MySQL tends to perform very well for simple primary-key reads and high-concurrency web traffic. PostgreSQL's query planner tends to handle complex joins, subqueries and analytics better. Both need tuning, indexing and monitoring to perform well in production.

Operationally, PostgreSQL creates a process per connection, so applications with many short-lived connections should use a pooler like PgBouncer. Both need regular maintenance, such as vacuuming in PostgreSQL and index and buffer pool tuning in MySQL. Nexzem defaults to PostgreSQL for new custom applications and keeps MySQL where a platform or existing team depends on it.

Final verdict

For new custom applications, PostgreSQL is usually the better default: its SQL depth, JSONB, extensions like PostGIS and pgvector, and permissive license give you more room to grow. MySQL remains an excellent choice for read-heavy web applications, PHP platforms like WordPress and teams with strong MySQL experience. Both are reliable, production-proven databases, so existing skills and platform requirements should weigh heavily in the decision.

PostgreSQL vs MySQL: questions

Something else on your mind? Ask a consultant and get a reply within one business day.

Is PostgreSQL better than MySQL?

PostgreSQL has more advanced features, including richer SQL, better JSON indexing, custom types and a powerful extension ecosystem. MySQL is simpler to operate and very fast for common read-heavy workloads. For complex or evolving applications, PostgreSQL is often the stronger choice; for standard web apps and MySQL-based platforms, MySQL works very well.

Is PostgreSQL faster than MySQL?

It depends on the workload. MySQL often has an edge on simple reads and very high numbers of lightweight connections. PostgreSQL usually performs better on complex queries, analytics and write-heavy workloads with concurrent transactions. Real performance depends far more on schema design, indexing and configuration than on the database choice itself.

How hard is it to migrate from MySQL to PostgreSQL?

Moderately hard. Schemas and data can be moved with tools like pgloader or AWS Database Migration Service, but SQL dialect differences, auto-increment handling, case sensitivity and stored procedures need changes. ORMs reduce the effort. Plan for a test migration, query review, performance testing and a cutover with rollback options.

Can PostgreSQL be used as a vector database?

Yes. The pgvector extension adds vector columns and similarity search with indexing methods such as HNSW and IVFFlat, which suits retrieval-augmented generation and semantic search. For many applications this avoids running a separate vector database. Very large vector collections or specialized search needs may still justify a dedicated vector database.

Still deciding between PostgreSQL and MySQL?

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