Database Management

PostgreSQL vs MySQL

Q: Is PostgreSQL or MySQL better for new applications?

PostgreSQL is the better default for new enterprise applications. MySQL remains preferable for high-volume read-mostly web workloads.

Q: Which is faster, PostgreSQL or MySQL?

Workload-dependent. MySQL InnoDB is faster on simple OLTP. PostgreSQL outperforms on complex joins, CTEs, and analytical queries.

Q: Can you migrate between PostgreSQL and MySQL?

Yes, using pgloader or AWS DMS. Stored procedures and vendor-specific SQL require rewrite. Typical projects take 1-6 months.

Q: Does PostgreSQL support vector search?

Yes, via pgvector with HNSW and IVFFlat indexing. It is the most widely used vector capability for RAG workloads on relational databases.

Q: What is the difference between Aurora PostgreSQL and standard PostgreSQL?

Aurora PostgreSQL is wire-compatible but uses a distributed storage engine. Some extensions are unavailable and the platform is AWS-only.

Independent comparison for enterprise buyers. Updated May 2026.

By the TechVendorIndex Editorial Team · Researched and reviewed against our scoring methodology

Quick verdict: Choose PostgreSQL for complex relational workloads requiring advanced features such as JSONB, partitioning, common table expressions, window functions, and extensions including PostGIS, pgvector, and Citus. Choose MySQL for high-volume web applications where read scalability, operational simplicity, and a mature LAMP-stack ecosystem matter more than feature breadth. The key differentiator is workload character: PostgreSQL excels at mixed analytical and transactional workloads; MySQL excels at read-heavy web-scale applications with simpler schemas.

Criteria	PostgreSQL	MySQL
Editorial score	4.6 / 5.0	4.3 / 5.0
Deployment	On-premise, all major clouds, managed services	Linux, Windows, all major clouds, managed services
Pricing Model	Open source (PostgreSQL licence); managed service or support optional	Open source (GPL) or commercial Enterprise Edition
Target Buyer	Complex schemas, mixed OLTP and analytics, modernisation programmes	Web-scale applications, SaaS backends, LAMP stack
Implementation	Approximately 1–4 months on managed services	Approximately 1–3 months on managed services
Customisation	PL/pgSQL, extension framework, foreign data wrappers, custom types	Standard SQL, stored procedures, simpler engine model
Ecosystem	pgAdmin, PostGIS, pgvector, TimescaleDB, Citus, Aurora PostgreSQL	MySQL Workbench, Aurora MySQL, MySQL HeatWave, broad ORM support
Key Strength	Standards compliance, extensions, complex query performance	Read-heavy scale, low operational overhead, ubiquity

How we researched this comparison. Assessments here synthesise vendor documentation, independent analyst coverage, and aggregated public review-platform sentiment, applied through our methodology. The Editorial score is TechVendorIndex's own editorial estimate — not a count of reviews we collected. How our scores work →

Feature comparison

PostgreSQL delivers the broader functional surface. ANSI SQL conformance is generally higher than MySQL, supporting features such as full common table expressions including recursive CTEs, advanced window functions, table inheritance, native JSONB with indexing, full-text search, materialised views, and arbitrary user-defined types. The extension framework is the standout architectural choice: PostGIS for spatial, pgvector for embedding storage and approximate nearest neighbour search, TimescaleDB for time series, Citus for distributed sharding, pg_partman for partition management, and hundreds of additional modules extend the engine without forking.

MySQL focuses on transactional simplicity and read-heavy performance. The InnoDB storage engine delivers ACID compliance, row-level locking, and crash recovery. MySQL 8.x added atomic DDL, descending indexes, CTEs, window functions, JSON path expressions, and replication improvements that closed several historical gaps with PostgreSQL. The MyISAM storage engine remains available for read-only workloads where ACID is not required. MySQL HeatWave on Oracle Cloud and AWS adds an in-memory analytics layer that lets MySQL serve OLTP and analytics on the same instance.

For high availability, PostgreSQL uses streaming or logical replication paired with Patroni, pg_auto_failover, or cloud-managed orchestration. MySQL offers InnoDB Cluster, Group Replication, and MySQL Router for similar capabilities. Amazon Aurora replaces the underlying storage layer entirely for both engines, delivering low replica lag and fast failover at the cost of being managed-service-only.

For analytics workloads, PostgreSQL's parallel query, partitioning, and JIT compilation handle complex analytical queries substantially better than stock MySQL. MySQL HeatWave closes this gap for OCI and AWS deployments. Both engines are used as OLTP sources for separate analytics warehouses such as Snowflake, BigQuery, Redshift, or Databricks.

For developer experience, PostgreSQL appeals to teams valuing standards compliance, predictable behaviour, and depth of features. MySQL appeals to teams valuing operational simplicity, ubiquitous tooling, and the maturity of the LAMP stack across PHP, Python, Ruby, and Node.js frameworks.

Pricing comparison

Both engines are free of licence cost in their open-source forms. PostgreSQL is released under the permissive PostgreSQL Licence, with no commercial fork dynamics. MySQL Community Edition is GPL; MySQL Enterprise Edition from Oracle lists at approximately $5,000 per server-year, MySQL Cluster CGE at approximately $10,000 per server-year. Commercial PostgreSQL support from EDB, Crunchy Data, or Percona typically runs $5,000–$15,000 per node annually. Managed services price by instance hours: Amazon RDS for PostgreSQL and MySQL price similarly at the same vCPU count; Aurora PostgreSQL is approximately 10-20% more expensive than Aurora MySQL on like-for-like workloads.

Five-year cost of ownership for a 32-core production deployment: self-managed PostgreSQL or MySQL Community $200K–600K largely staffing, managed PostgreSQL or MySQL on a hyperscaler $400K–1.2M, Aurora $500K–1.5M. The primary buying-side caveat for MySQL is dual licensing: any MySQL-derived product distributed commercially without GPL compliance requires an Enterprise licence from Oracle, which has triggered audit recovery in past acquisitions. PostgreSQL has no equivalent contractual risk; vendor support contracts are optional and avoidable. Pricing as of May 2026.

When to choose PostgreSQL

Choose PostgreSQL for complex relational workloads requiring advanced SQL features, mixed OLTP and analytical query patterns, applications using PostGIS for geospatial data, pgvector for retrieval-augmented generation embeddings, TimescaleDB for time series, or Citus for distributed sharding, when migrating from Oracle Database or SQL Server and seeking maximum SQL compatibility, when ANSI SQL conformance and predictable behaviour matter, or when targeting managed services such as Amazon Aurora PostgreSQL, Azure Database for PostgreSQL Flexible Server, or Google AlloyDB as the production platform.

When to choose MySQL

Choose MySQL for web-scale applications and SaaS backends where read-heavy workloads, simple schema designs, and operational simplicity dominate, for LAMP-stack development on PHP, Python, Ruby, or Node.js, when targeting managed services such as Amazon RDS for MySQL, Aurora MySQL, Azure Database for MySQL Flexible Server, or Google Cloud SQL for MySQL, when the operational team has deeper MySQL experience than PostgreSQL experience, for embedded applications where MySQL Community's GPL terms align, or when running MySQL-compatible managed services such as PlanetScale or MySQL HeatWave.

Alternatives to both

Microsoft SQL Server

Microsoft stack integration with deep BI tooling

4.5

Oracle Database

Mission-critical OLTP with RAC and Exadata

4.4

Amazon Aurora

Managed PostgreSQL or MySQL with separated storage

4.5

CockroachDB

PostgreSQL-compatible distributed SQL for global scale

4.3

Full PostgreSQL Review Full MySQL Review All Database Management

Frequently Asked Questions

Is PostgreSQL or MySQL better for new applications?

PostgreSQL is generally the better default for new enterprise applications due to broader SQL compliance, richer data types, and the extension ecosystem. MySQL remains preferable for high-volume read-mostly web applications and for teams with deeper MySQL operational experience or LAMP-stack tooling.

Which is faster, PostgreSQL or MySQL?

Performance is workload-dependent. MySQL with InnoDB tends to be faster for simple read-heavy OLTP and high-concurrency point lookups. PostgreSQL tends to outperform on complex queries involving joins, CTEs, window functions, and analytical workloads. Both engines are highly performant when tuned to the workload.

Can you migrate between PostgreSQL and MySQL?

Yes, but stored procedures, triggers, and any vendor-specific SQL require rewrite. Schema and data migration is well-supported by tools such as pgloader for MySQL to PostgreSQL and AWS Database Migration Service in both directions. Typical migration projects run 1-6 months per application depending on complexity.

Does PostgreSQL support vector search?

Yes, through the pgvector extension, which adds a vector data type and approximate nearest neighbour search using HNSW and IVFFlat indexing. Pgvector is the most widely used vector capability for retrieval-augmented generation workloads built on relational databases. MySQL added native vector support in version 9 with more limited indexing options.

What is the difference between Aurora PostgreSQL and standard PostgreSQL?

Amazon Aurora PostgreSQL is wire-compatible with PostgreSQL but replaces the storage engine with a distributed log-structured store that delivers low replica lag, six-way replication, and rapid failover. Some PostgreSQL extensions are not available on Aurora, and the platform is AWS-only with corresponding migration constraints.

Last updated: May 2026