Decision comparison
PostgreSQL vs MySQL
PostgreSQL delivers superior SQL compliance, advanced indexing, and extensibility that make it the stronger choice for complex analytical workloads and data integrity requirements. MySQL wins on ease of adoption, massive community scale, and Oracle-backed enterprise features like HeatWave and built-in ML. Both databases are open-source, battle-tested, and capable of powering production applications at any scale.
Direct comparison. These are reviewed substitutes bought for the same job, so the differences below are the ones that decide between them.
All 2 are relational databases.
Quick Comparison
| Decision factor | PostgreSQL | MySQL |
|---|---|---|
| Best For | Data teams running complex analytics, geospatial queries, or workloads requiring strict ANSI SQL compliance and extensibility | Web application teams prioritizing fast setup, massive hosting ecosystem, and Oracle-backed cloud analytics and ML capabilities |
| Pricing | Fully open-source with community support free; enterprise support and services available for a fee | Contact for pricing |
| SQL Compliance | Strong ANSI SQL compliance with advanced window functions, CTEs, materialized views, and native parallel query execution | Good baseline SQL support with CTEs and set operations; lacks native materialized views and has historically looser compliance |
| Scalability | Handles large analytical workloads with parallel query, range/list/hash partitioning, and multiversion concurrency control | MySQL Cluster CGE for high-availability transactional workloads; HeatWave adds cloud-based lakehouse-scale analytics processing |
| Data Types & Extensibility | Object-relational model with JSONB, custom data domains, GiST and R-tree indexes, and 35+ years of extensibility | Traditional relational model with blob/clob support and type inference; extensibility limited compared to PostgreSQL's object model |
| Community & Ecosystem | 21,000+ GitHub stars with active development through version 18; BSD-licensed with fully independent community governance | 12,000+ GitHub stars; owned by Oracle with 2,000+ OEM/ISV partners embedding MySQL in commercial products worldwide |
PostgreSQL
- Best For:
- Data teams running complex analytics, geospatial queries, or workloads requiring strict ANSI SQL compliance and extensibility
- Pricing:
- Fully open-source with community support free; enterprise support and services available for a fee
- SQL Compliance:
- Strong ANSI SQL compliance with advanced window functions, CTEs, materialized views, and native parallel query execution
- Scalability:
- Handles large analytical workloads with parallel query, range/list/hash partitioning, and multiversion concurrency control
- Data Types & Extensibility:
- Object-relational model with JSONB, custom data domains, GiST and R-tree indexes, and 35+ years of extensibility
- Community & Ecosystem:
- 21,000+ GitHub stars with active development through version 18; BSD-licensed with fully independent community governance
MySQL
- Best For:
- Web application teams prioritizing fast setup, massive hosting ecosystem, and Oracle-backed cloud analytics and ML capabilities
- Pricing:
- Contact for pricing
- SQL Compliance:
- Good baseline SQL support with CTEs and set operations; lacks native materialized views and has historically looser compliance
- Scalability:
- MySQL Cluster CGE for high-availability transactional workloads; HeatWave adds cloud-based lakehouse-scale analytics processing
- Data Types & Extensibility:
- Traditional relational model with blob/clob support and type inference; extensibility limited compared to PostgreSQL's object model
- Community & Ecosystem:
- 12,000+ GitHub stars; owned by Oracle with 2,000+ OEM/ISV partners embedding MySQL in commercial products worldwide
Public signals
Verified factual signals only. Bars appear only for like-for-like metrics with five weekly assessments for every tool; missing evidence stays explicit. These signals do not establish enterprise adoption, product quality, or total cost.
| Metric | PostgreSQL | MySQL |
|---|---|---|
| Docker Hub pulls(Product adoption) | 11.6B | 5.1B |
| GitHub commits, 90d(Developer adoption) | 899 | Not available |
| GitHub stars(Developer adoption) | 22,000+ | Not available |
| Search interest(Market interest) | 59 | 64 |
| Hacker News mentions, 90d(Community interest) | 181 | 51 |
| npm weekly downloads(Ecosystem adoption) | 38.5M | 10.6M |
| PyPI weekly downloads(Ecosystem adoption) | 12.6M | Not available |
| Stack Overflow questions(Community interest) | 178.8k | 657.1k |
| GitHub commits, 90d(Product adoption) | Not available | 657 |
| GitHub stars(Product adoption) | Not available | 12,000+ |
| Product Hunt comments(Community interest) | Not available | 2 |
| Product Hunt rating(Community interest) | Not available | 5.0/5 |
| Product Hunt reviews(Community interest) | Not available | 7 |
| Product Hunt votes(Community interest) | Not available | 7 |
| PyPI weekly downloads(Developer adoption) | Not available | 6.8M |
As of September 21, 2026 — updated weekly.
Health & risk evidence
Observed public-source checks for mapped package versions and repositories.
PostgreSQL
September 21, 2026Package vulnerabilities
npm · pg@8.23.0 · PyPI · psycopg2@2.9.13
0 vulnerabilities
across 2 packages
Repository security score
github.com/postgres/postgres
6.1/10
MySQL
September 21, 2026Package vulnerabilities
PyPI · mysql-connector-python@26.7.0 · npm · mysql2@3.24.4
0 vulnerabilities
across 2 packages
Repository security score
Not available
Feature Comparison
| Feature | PostgreSQL | MySQL |
|---|---|---|
| Query Capabilities | ||
| Window Functions | Full windowing function support for ranking, aggregation, and running calculations across result sets | Window functions added in MySQL 8.0 covering standard ranking and aggregate operations |
| Common Table Expressions | Recursive and non-recursive CTEs for hierarchical queries and complex subquery factoring | Recursive and non-recursive CTEs supported since MySQL 8.0 for hierarchical data traversal |
| Parallel Query Execution | Native parallel query distributes sequential scans and joins across multiple CPU cores automatically | Limited parallelism in Community Edition; HeatWave provides massively parallel cloud-based query processing |
| Indexing & Performance | ||
| Index Types | B-tree, hash, GiST, R-tree, bitmap, and composite range-plus-hash indexes for diverse workloads | B-tree and hash indexes with composite range-plus-hash partitioning for standard query optimization |
| Materialized Views | Native materialized views store precomputed query results and refresh on demand for fast analytical reads | No built-in materialized views; teams use summary tables with triggers or scheduled refresh scripts |
| Concurrency Control | MVCC ensures readers never block writers with snapshot isolation across all table types natively | MVCC available through InnoDB engine providing row-level locking and consistent read snapshots |
| Data Integrity & Types | ||
| ACID Compliance | Full ACID compliance across all operations including DDL statements with transactional safety guaranteed | ACID compliance through InnoDB storage engine; MyISAM engine historically sacrificed ACID for read speed |
| Referential Integrity | Enforced foreign key constraints with cascading updates and deletes across all table types | Foreign key support in InnoDB; historically weaker enforcement when using MyISAM or mixed engines |
| Custom Data Domains | User-defined data domains allow creating reusable constrained types for consistent validation across tables | Standard column types with CHECK constraints available; no native custom domain type definitions supported |
| Programmability | ||
| Stored Procedures | PL/pgSQL procedures with exception handling, dynamic SQL, and support for multiple procedural languages | Stored procedures and functions using SQL and a proprietary procedural language with basic control flow |
| Triggers | Row-level and statement-level triggers firing before, after, or instead of insert/update/delete operations | Row-level triggers supporting before and after events on insert, update, and delete operations |
| Cursors | Scrollable and non-scrollable server-side cursors for iterating through large result sets efficiently | Read-only server-side cursors for sequential row-by-row processing within stored procedures |
| Platform & Security | ||
| Platform Support | Runs on Linux, macOS, Windows, UNIX, AmigaOS, and Android covering all major operating systems | Runs on Linux, macOS, Windows, UNIX, z/OS, AmigaOS, and Android including mainframe support |
| Access Control | Role-based access control with row-level security, column encryption, and brute-force connection protection | Attribute-based access control with enterprise directory compatibility and SSL-encrypted connections |
| Machine Learning Integration | ML integration through extensions like MADlib and PL/Python for in-database model training and scoring | MySQL AI and HeatWave AutoML provide integrated automated machine learning directly within the database |
Query Capabilities
Window Functions
Common Table Expressions
Parallel Query Execution
Indexing & Performance
Index Types
Materialized Views
Concurrency Control
Data Integrity & Types
ACID Compliance
Referential Integrity
Custom Data Domains
Programmability
Stored Procedures
Triggers
Cursors
Platform & Security
Platform Support
Access Control
Machine Learning Integration
Which to choose
PostgreSQL delivers superior SQL compliance, advanced indexing, and extensibility that make it the stronger choice for complex analytical workloads and data integrity requirements. MySQL wins on ease of adoption, massive community scale, and Oracle-backed enterprise features like HeatWave and built-in ML. Both databases are open-source, battle-tested, and capable of powering production applications at any scale.
Best-fit scenarios
Choose PostgreSQL if:
Data teams running complex analytics, geospatial queries, or workloads requiring strict SQL compliance
Choose MySQL if:
Web application teams prioritizing fast setup, massive ecosystem support, and cloud-native ML capabilities
These scenarios reflect the available product evidence. Your requirements, existing stack, and team expertise should guide the final decision.
Frequently Asked Questions
What are the main technical differences between PostgreSQL and MySQL?
PostgreSQL is an object-relational database with over 35 years of development, offering advanced features like native materialized views, GiST and R-tree indexing, parallel query execution, custom data domains, and full ACID compliance across all operations including DDL. MySQL is a traditional relational database that provides ACID compliance through its InnoDB storage engine but historically offered the faster-but-less-safe MyISAM engine as well. PostgreSQL supports richer SQL syntax including advanced window functions and set operations, while MySQL focuses on high-speed read operations and ease of deployment for web applications.
Is PostgreSQL really free, and what does MySQL Enterprise Edition cost?
PostgreSQL is completely free and open-source under a BSD-style license with $0 licensing cost for any use case, including commercial production deployments. Community support through mailing lists and documentation is free, while third-party vendors offer paid enterprise support packages. MySQL Community Edition is also free and open-source, but Oracle offers MySQL Enterprise Edition with advanced features like enterprise directory compatibility, enhanced security, and management tools at a per-server price that requires contacting Oracle sales. MySQL HeatWave, the cloud analytics add-on, carries separate cloud service pricing.
Which database is better for handling large-scale data warehousing workloads?
PostgreSQL has stronger native capabilities for data warehousing with parallel query execution that distributes work across CPU cores, native materialized views for precomputed aggregations, advanced partitioning through range, list, hash, and composite strategies, and bitmap indexing for analytical queries. MySQL approaches large-scale analytics differently through HeatWave, which offloads queries to a massively parallel cloud processing engine for lakehouse-scale analytics. For on-premises data warehousing, PostgreSQL provides more built-in analytical tooling. For cloud-native analytics at massive scale, MySQL HeatWave offers a managed solution with automated ML built in.
How do PostgreSQL and MySQL compare in terms of community support and long-term viability?
PostgreSQL has 21,000+ GitHub stars and is governed by an independent community with no single corporate owner, ensuring decisions are made purely on technical merit. It maintains active development through version 18 with regular releases. MySQL has 12.4k GitHub stars and is owned by Oracle, which provides substantial engineering resources but introduces vendor dependency concerns. MySQL benefits from the largest installed base of any open-source database, powering major platforms like Facebook, Twitter, YouTube, and Netflix. Both have vibrant ecosystems with conferences, user groups, and extensive documentation, but PostgreSQL's independent governance appeals to teams wary of corporate control.