Technology comparison

PostgreSQL vs MySQL: data models, performance & use cases

Choose PostgreSQL when you need advanced SQL features, strong data integrity, rich indexing (GIN, GiST, BRIN), native JSONB queries, or extensibility such as PostGIS, and you can accept somewhat more tuning effort. Choose MySQL when your priority is a simple, widely available relational database with mature read-heavy replication, broad managed hosting and ecosystem familiarity, especially for conventional web applications. Either can serve most workloads; validate with your own schema, query patterns, and operational constraints before committing.

Technical context and trade-offs

These differences are drawn directly from the comparison criteria below.

SQL standards and feature depth

PostgreSQL: PostgreSQL adheres closely to SQL standards and offers a deep feature set, including window functions, common table expressions, full outer joins, lateral joins, range types, and set-returning functions. These capabilities are available across supported versions and are documented in the official manual, though exact behavior can vary by major version.

MySQL: MySQL supports core SQL and has improved standards conformance over time, adding window functions and CTEs in MySQL 8.0. Some advanced constructs remain less complete or behave differently than in PostgreSQL, and features depend on the storage engine in use.

JSON and semi-structured data

PostgreSQL: PostgreSQL provides native JSON and JSONB types, with JSONB stored in a decomposed binary format that supports indexing, containment operators, and path queries. GIN indexes on JSONB make it practical for document-style workloads, and functionality has expanded in recent releases.

MySQL: MySQL offers a JSON data type with functions for extraction and manipulation, plus multi-valued indexes that can accelerate certain JSON queries in MySQL 8.0 and later. It is workable for storing documents but generally considered less flexible for complex indexing and querying than PostgreSQL's JSONB approach.

Quick verdictThe bottom line

PostgreSQLMySQLExplore the detailed comparison

Scores by criterion

Performance50–50 (1 criteria)

Ease of useNo direct evidence in the criteria

Ecosystem100–0 (1 criteria)

PopularityNo direct evidence in the criteria

PostgreSQLMySQL

Scores reflect wins in matching criteria; ties count as half a point.

Technical feature matrix

Criterion	PostgreSQL	MySQL	Edge
SQL standards and feature depth	PostgreSQL adheres closely to SQL standards and offers a deep feature set, including window functions, common table expressions, full outer joins, lateral joins, range types, and set-returning functions. These capabilities are available across supported versions and are documented in the official manual, though exact behavior can vary by major version.	MySQL supports core SQL and has improved standards conformance over time, adding window functions and CTEs in MySQL 8.0. Some advanced constructs remain less complete or behave differently than in PostgreSQL, and features depend on the storage engine in use.	PostgreSQL
JSON and semi-structured data	PostgreSQL provides native JSON and JSONB types, with JSONB stored in a decomposed binary format that supports indexing, containment operators, and path queries. GIN indexes on JSONB make it practical for document-style workloads, and functionality has expanded in recent releases.	MySQL offers a JSON data type with functions for extraction and manipulation, plus multi-valued indexes that can accelerate certain JSON queries in MySQL 8.0 and later. It is workable for storing documents but generally considered less flexible for complex indexing and querying than PostgreSQL's JSONB approach.	PostgreSQL
Indexing and query planning	PostgreSQL supports B-tree, hash, GIN, GiST, SP-GiST, and BRIN indexes, enabling specialized access paths for full-text search, arrays, geospatial data, and large append-only tables. The planner is generally sophisticated, and extensive statistics and configuration settings let you tune plans, though optimal results require expertise.	MySQL relies primarily on B-tree indexes, including full-text and spatial indexes on supported storage engines such as InnoDB. Its optimizer is effective for common OLTP queries, but the range of index types and planner controls is narrower than PostgreSQL's.	PostgreSQL
Replication and high availability	PostgreSQL offers streaming replication with synchronous and asynchronous modes, logical replication for selective data replication, and third-party tools for clustering and failover. Built-in features are robust, while automated failover typically depends on external tooling and careful configuration.	MySQL has long-standing, widely deployed replication, including asynchronous and semi-synchronous replication and Group Replication for multi-primary or high-availability topologies. Its replication ecosystem is mature and well documented, and managed services commonly offer automated failover, though behavior depends on the specific version and topology.	MySQL
Extensibility and ecosystem	PostgreSQL allows extensions to add types, functions, operators, and index methods, with notable examples including PostGIS for geospatial data, pgvector for vector similarity, and TimescaleDB for time-series workloads. Its extension ecosystem is a major differentiator, though extension availability varies by hosting provider.	MySQL has a large ecosystem of tools, connectors, and managed services, and supports pluggable storage engines. However, it does not offer a comparable extension mechanism for adding custom types and index methods, so specialized workloads often require separate systems.	PostgreSQL
Performance and concurrency	PostgreSQL uses MVCC with multi-version concurrency control that avoids read locks, and it performs well on complex queries, analytics, and mixed workloads when properly tuned. Write-heavy workloads can require attention to vacuum and bloat management, and performance depends heavily on configuration and hardware.	MySQL with InnoDB generally delivers strong performance for read-heavy OLTP applications and simple primary-key lookups, and its defaults are often approachable. Performance on complex analytical queries can be lower than PostgreSQL's, though results vary by version, schema, indexes, and tuning.	Comparable
Licensing, hosting, and operational familiarity	PostgreSQL is released under the permissive PostgreSQL License, and major cloud providers offer managed services with varying feature support. It is widely used, but some teams find its configuration and tuning surface larger than MySQL's.	MySQL Community Edition is available under the GPL, while commercial editions use a separate license, and managed MySQL is offered by most cloud providers. It has a very large talent pool and abundant hosting options, which can lower operational friction for conventional applications.	MySQL

When to choose each option

Choose this option if… PostgreSQL

Choose PostgreSQL when the strengths described here match your project requirements. SQL standards and feature depth: PostgreSQL adheres closely to SQL standards and offers a deep feature set, including window functions, common table expressions, full outer joins, lateral joins, range types, and set-returning functions. These capabilities are available across supported versions and are documented in the official manual, though exact behavior can vary by major version. JSON and semi-structured data: PostgreSQL provides native JSON and JSONB types, with JSONB stored in a decomposed binary format that supports indexing, containment operators, and path queries. GIN indexes on JSONB make it practical for document-style workloads, and functionality has expanded in recent releases. Indexing and query planning: PostgreSQL supports B-tree, hash, GIN, GiST, SP-GiST, and BRIN indexes, enabling specialized access paths for full-text search, arrays, geospatial data, and large append-only tables. The planner is generally sophisticated, and extensive statistics and configuration settings let you tune plans, though optimal results require expertise.

Choose this option if… MySQL

Choose MySQL when the strengths described here match your project requirements. Replication and high availability: MySQL has long-standing, widely deployed replication, including asynchronous and semi-synchronous replication and Group Replication for multi-primary or high-availability topologies. Its replication ecosystem is mature and well documented, and managed services commonly offer automated failover, though behavior depends on the specific version and topology. Licensing, hosting, and operational familiarity: MySQL Community Edition is available under the GPL, while commercial editions use a separate license, and managed MySQL is offered by most cloud providers. It has a very large talent pool and abundant hosting options, which can lower operational friction for conventional applications.

Technology role diagram

Option A

PostgreSQL

Databases

Option B

MySQL

Databases

This diagram shows broad areas of use, not a complete deployment architecture.

Code examples

PostgreSQL

const { Client } = require('pg');

async function main() {
  const client = new Client({ connectionString: 'postgresql://postgres:postgres@localhost:5432/postgres' });
  await client.connect();
  await client.query('CREATE TABLE IF NOT EXISTS greetings (id serial PRIMARY KEY, message text NOT NULL)');
  await client.query('INSERT INTO greetings (message) VALUES ($1)', ['Hallo, Welt!']);
  const res = await client.query('SELECT message FROM greetings LIMIT 1');
  console.log(res.rows[0]);
  await client.end();
}

main().catch(console.error);

Frequently asked questions

Is PostgreSQL or MySQL better for a new web application in 2026?

Both are viable for typical web applications. PostgreSQL is often preferred when you expect complex queries, strong data integrity constraints, JSONB documents, or future extension needs such as geospatial data. MySQL is a reasonable choice for conventional read-heavy applications where team familiarity, broad managed hosting, and simple operational patterns matter most. Evaluate your actual query patterns and hosting constraints rather than choosing by reputation alone.

Does MySQL support advanced SQL features like window functions and CTEs?

Yes. MySQL 8.0 introduced window functions and common table expressions, closing several historical gaps with PostgreSQL. Some advanced constructs, such as certain join types and specialized index methods, remain more limited in MySQL, so check feature availability against your target MySQL version and storage engine before relying on them.

Which database handles JSON data better?

PostgreSQL generally offers more capable JSON handling through its JSONB type, which supports indexing with GIN, containment queries, and flexible path operations. MySQL's JSON type and multi-valued indexes are adequate for many document-oriented use cases, especially in MySQL 8.0 and later. The better choice depends on how heavily you query and index nested JSON structures.

Is PostgreSQL harder to operate than MySQL?

PostgreSQL exposes many configuration parameters and requires attention to autovacuum and bloat, which can feel more complex to teams new to it. MySQL often has simpler defaults for common OLTP workloads and a large body of operational knowledge. Managed services reduce this gap substantially for both databases, so operational difficulty depends on your provider and workload.

How do replication and high availability compare?

MySQL has a mature replication ecosystem, including Group Replication and widely offered managed failover, which makes it attractive for standard high-availability deployments. PostgreSQL provides robust streaming and logical replication, but automated failover commonly relies on external tooling. In both cases, verify the specific capabilities of your chosen version and hosting provider.

Can I use PostgreSQL extensions on managed cloud services?

Many managed PostgreSQL services support a curated set of extensions such as PostGIS and pgvector, but availability differs by provider and plan. Some extensions may be restricted, require specific versions, or be unavailable entirely. Confirm the extension list for your target service before designing around one.

Which database performs better under heavy write loads?

Performance depends on schema, indexes, transaction size, hardware, and tuning, so neither database wins universally. MySQL with InnoDB is often efficient for high-throughput simple writes, while PostgreSQL handles concurrent mixed workloads well but needs proper vacuum configuration. Benchmark with your own workload rather than relying on general claims.

Do both databases work well with popular frameworks and ORMs?

Yes. PostgreSQL and MySQL are both widely supported by major frameworks, ORMs, and migration tools across languages. Differences tend to appear in feature-specific behavior, such as JSON operators or upsert syntax, rather than in basic connectivity. Choose based on the features you need and confirm your framework's support for those features.