Migrating from PostgreSQL to MySQL [2025 Guide]

Choosing the right database is critical for any organization. Two of the best open-source options are MySQL and PostgreSQL.

MySQL is known for its speed and ease of use, making it a popular choice for web applications and content management systems.
PostgreSQL, renowned for its robustness, advanced features, and scalability, is often favored for complex applications and data warehousing.

Both are powerful relational database management systems (RDBMS) that use SQL (Structured Query Language) for data manipulation. However, they differ in aspects like data types, performance characteristics, and the level of complexity they can handle.

This article will guide you through a comparison of these two databases, explore reasons for using both, and provide insights into the migration process from PostgreSQL to MySQL.

What are MySQL and PostgreSQL?

Both MySQL and PostgreSQL are widely-used database systems that store and manage data for various applications.

SQL is the standard language for interacting with relational databases. This includes:
- Defining tables with specified data types (like integers, text, dates)
- Manipulating data through commands like INSERT, UPDATE, and DELETE
- Retrieving data using SELECT queries RDBMS like MySQL and PostgreSQL organize data into tables with rows and columns. Relationships between tables are established using primary keys and foreign keys, ensuring data integrity and consistency.
MySQL is a popular open-source database system known for its speed, ease of use, and wide community support. It's often the preferred choice for web applications and content management systems.
PostgreSQL is another powerful open-source database system that offers a rich feature set including advanced data types like JSON and arrays, robust support for complex queries, and strong support for extensibility. It's a great choice for demanding applications such as data warehousing, geospatial analysis, and applications requiring high availability and fault tolerance.

Both systems can be managed by database administrators (DBAs) who are responsible for tasks such as performance tuning, security management, and ensuring data availability.

Beyond PostgreSQL and MySQL

The database landscape includes other prominent players:

Oracle Database: A commercial, enterprise-grade database system known for its reliability and security.
MongoDB: A popular NoSQL database, offering a flexible schema and well-suited for handling unstructured and semi-structured data.
Microsoft SQL Server: Another widely-used commercial database system, often integrated into the Microsoft ecosystem.

The choice of database depends on various factors such as the specific needs of the application, the volume and type of data, the required performance and scalability, and available budget and resources.

Key Differences Between MySQL and PostgreSQL

SQL is the standard language for interacting with relational databases.
While both use SQL, there are subtle differences in their SQL syntax and the specific features they support. For instance:
- PostgreSQL offers more advanced features like full-text search capabilities.
- PostgreSQL provides robust support for advanced data types such as arrays and JSONB.
Partitioning, another key feature, allows you to divide large tables into smaller, more manageable chunks, improving query performance and simplifying maintenance.
Both databases prioritize data integrity through mechanisms like constraints (such as primary and foreign keys) and transactions.
Performance variations can occur depending on the specific workload, complexity of queries, data volume, and underlying hardware (like CPU and memory). Choosing Between MySQL and PostgreSQL

When choosing between MySQL and PostgreSQL, consider:

The specific use cases
The nature of the dataset
The anticipated workloads
Data types required by the application (such as timestamps, booleans, and varchar strings)
The available ecosystem of tools, drivers, and third-party providers
The level of community and vendor support required
MySQL generally excels in scenarios involving high-volume transactions and web applications with frequent read and write operations.
PostgreSQL is well-suited for complex applications that require advanced features such as full-text search, support for specialized data types like arrays and JSONB, and robust handling of large datasets.

Side-By-Side Comparison of PostgreSQL and MySQL

Feature	MySQL	PostgreSQL
Open Source	Yes	Yes
Speed	Generally faster for simpler queries	Can be faster for complex queries and large datasets
Ease of Use	Often considered more user-friendly	Can have a steeper learning curve due to its advanced features
Scalability	Highly scalable	Highly scalable, with features like partitioning and parallel query execution
Data Types	Supports a wide range of data types	Supports a wider range of data types, including advanced types like arrays, JSONB, and spatial data
Full-Text Search	Basic support	Robust full-text search capabilities
JSON Support	Supports JSON data	Supports JSON and JSONB (optimized for storage and querying of JSON data)
Partitioning	Available	Available, with more advanced partitioning options
Security	Good security features	Strong security features, including row-level security and encryption
Community Support	Large and active community	Large and active community, but may be smaller than MySQL's
Use Cases	Web applications, content management systems, e-commerce	Complex applications, data warehousing, geospatial applications, financial applications

Why Use Both PostgreSQL and MySQL?

Companies may utilize both PostgreSQL and MySQL within their infrastructure for various reasons:

Scalability: PostgreSQL excels in handling large datasets and high-volume workloads.
Concurrency: PostgreSQL offers robust features to handle multiple simultaneous transactions and ensure data consistency.
Real-Time: PostgreSQL can provide an edge for applications requiring real-time data processing and low latency.
Caching: MySQL can be used as a caching layer for read-heavy workloads, while PostgreSQL serves as the primary data store.
Replication: Both databases support replication, allowing for high availability and disaster recovery.

By strategically deploying both databases, companies can leverage the strengths of each system, optimizing their infrastructure for different use cases and improving overall performance, scalability, and reliability.

Overview of PostgreSQL

PostgreSQL is a powerful, open-source object-relational database system known for its robustness, advanced features, and extensibility.
PostgreSQL Database: Stores and manages data in a structured format. It supports a wide range of data types, including integers, text, dates, and complex objects like arrays and JSON.
Linux: PostgreSQL is highly compatible with Linux operating systems.
Python: PostgreSQL integrates well with various programming languages, including Python.
psql: This is the command-line interface for PostgreSQL.

Overview of MySQL

MySQL is a popular open-source relational database system known for its speed, ease of use, and wide community support.
MySQL Database: Stores and manages data in a structured format. It utilizes tables to organize data, where each table consists of rows and columns.
MySQL Table: A fundamental unit of data organization in MySQL.
InnoDB: The default storage engine for MySQL, known for its support for transactions, row-level locking, and high performance.
MariaDB: A community-developed fork of MySQL.
CSV: MySQL supports importing and exporting data in CSV (Comma-Separated Values) format.
Synchronous: MySQL replication can be configured in synchronous mode.
PHP: MySQL integrates seamlessly with PHP.
Backend: MySQL often serves as the backend database for web applications.
Apache: MySQL frequently works in conjunction with Apache, a popular web server.
Web Applications: MySQL is a cornerstone for building a wide range of web applications.
GitHub: MySQL is an open-source project, and its source code is available on GitHub.

Migrating From PostgreSQL to MySQL

Migrating from PostgreSQL to MySQL can be necessary for various reasons, such as cost optimization, performance improvements, or to better align with the existing infrastructure. Several methods can be employed:

No-Code Data Integration Platform: These platforms provide user-friendly interfaces that streamline the migration process.
Custom Code: For complex migration scenarios or when high customization is required.
Open Source Software: Several open-source tools are available to facilitate data migration between PostgreSQL and MySQL.
Exporting Data & Reimporting It Using Files: This method involves exporting data from PostgreSQL in a suitable format, such as CSV or SQL files, and then importing it into MySQL.

5 Tools For PostgreSQL to MySQL Data Replication

The choice of migration method will depend on factors such as the size and complexity of the dataset, the available resources, the desired level of automation, and the specific requirements of the project.

Here are 5 tools for migrating data from PostgreSQL to MySQL

Portable (Coming Soon)
Streamkap
Keboola
Hevo Data
Integrate.io

Conclusion

Migrating from PostgreSQL to MySQL requires careful planning and consideration.

Evaluate your specific requirements: Analyze your application's needs, data volume, and performance expectations.
Research and compare migration tools: Explore the available options and select the best fit for your project.
Plan and test: Develop a detailed migration plan, including data mapping, testing procedures, and rollback strategies.
Monitor and optimize: After migration, monitor the performance of the MySQL database and make necessary adjustments to optimize performance and ensure data integrity.

By carefully assessing your needs and choosing the right approach, you can successfully migrate from PostgreSQL to MySQL and reap the benefits of this powerful open-source database system.