Postgree vs MySQL: An Exclusive Guide to Database Selection

When it comes to selecting a database management system (DBMS), the debate often centers around Postgree vs MySQL. Both are immensely popular open-source SQL databases with strong community support and extensive documentation. However, they have their unique strengths and use cases. In this guide, we’ll dive into the performance characteristics, scenarios for use, and a comparative overview including query examples to help you make an informed decision.

Understanding PostgreSQL and MySQL

PostgreSQL, often known as Postgres, is an object-relational database management system (ORDBMS) with an emphasis on extensibility and standards compliance. It is designed to handle a range of workloads, from single machines to data warehouses or Web services with many concurrent users.

MySQL, on the other hand, is a relational database management system (RDBMS) based on SQL (Structured Query Language). It is renowned for its reliability, simplicity, and speed. MySQL is a go-to choice for web-based applications and is an integral component of the LAMP (Linux, Apache, MySQL, PHP/Python/Perl) stack.

Performance Comparison

When comparing performance, it’s important to consider specific use cases, as the advantages of each DBMS can vary depending on the workload, especially in the context of Postgree vs MySQL.

Read-heavy Workloads

For applications with read-heavy operations, MySQL tends to perform faster due to its simpler and faster row-level locking mechanism. MySQL’s default storage engine, InnoDB, is optimized for high read volumes and can efficiently manage concurrent reads.

Write-heavy Workloads

PostgreSQL excels in environments with complex write-heavy operations or when handling large datasets. Its advanced MVCC (Multi-Version Concurrency Control) feature allows for concurrent writes by creating a new version of a data row for every transaction, thus reducing lock contention.

Complex Queries

PostgreSQL supports a wider range of SQL standards and includes features like Common Table Expressions (CTEs) and window functions, making it more suitable for complex queries and data analysis tasks.


PostgreSQL offers powerful JSON support, allowing for efficient storage and querying of JSON data types. This makes it an excellent choice for applications that require flexible data models or deal with semi-structured data.

Use Cases

When to Use MySQL:

  • Web-based applications, especially those in the LAMP stack.
  • Projects that require a fast and reliable DBMS for simple queries.
  • Applications where read performance is more critical than write complexity.

When to Use PostgreSQL:

  • Applications requiring complex queries, data warehousing, or analytical operations.
  • Projects that need strong compliance with SQL standards.
  • Use cases that benefit from PostgreSQL’s extensive support for different data types, such as geometric/GIS data processing.

Query Examples for Postgree vs MySQL

Let’s look at a basic query example to see how both databases handle a simple select operation.


SELECT * FROM users WHERE age > 25 ORDER BY lastname;


SELECT * FROM users WHERE age > 25 ORDER BY lastname;

At the surface level, basic SQL syntax is quite similar between both databases. However, PostgreSQL’s advanced features allow for more complex and nuanced queries. For example, PostgreSQL can handle complex data types and operations directly within SQL queries, such as querying JSON data:

PostgreSQL JSON Query:

    info ->> 'name' AS name 
    info -> 'age' > '25';

MySQL has introduced JSON support in its later versions but with different syntax and capabilities. For equivalent operations, the queries might need to be adjusted, and performance can vary based on the complexity of the data and operations.


Both PostgreSQL and MySQL offer robust solutions for managing databases, but your project’s specific needs should guide your choice. For complex transactions, analytical processes, or if you’re working with multi-faceted data types, PostgreSQL might be the way to go. On the other hand, for read-heavy applications or when working within the LAMP stack, MySQL could offer a more straightforward and performant solution. When making this decision, it’s crucial to consider the strengths and weaknesses of each, especially when comparing Postgree vs MySQL, to ensure the optimal fit for your project.

Ultimately, the decision between PostgreSQL and MySQL should be informed by your application’s requirements, the complexity of the data and queries involved, and the database system’s performance under those specific conditions, particularly when comparing Postgree vs MySQL. Experimentation and benchmarking based on real-world scenarios relevant to your project are the best ways to make an informed decision.