How to Migrate a PostgreSQL Database to MySQL

Moving a database from one platform to another can be tough, but with careful planning and execution, it can be done smoothly.

In this article, we'll go over how to migrate a PostgreSQL database to MySQL, which are both popular RDBMS. We'll cover preparation, schema conversion, data migration, and testing, using detailed examples and outputs to help beginners understand the process.

Schema Differences between PostgreSQL and MySQL

In our PostgreSQL setup, we manage three tables: "items" for inventory details, "clients" for customer information, and "purchases" for order records.

Here's how the "items" table is structured in PostgreSQL:

SQL

CREATE TABLE items
(
 id SERIAL, 
name VARCHAR, 
description VARCHAR, 
price INTEGER 
);

SERIAL in Postgres vs MySQL

In PostgreSQL, SERIAL is a pseudo-type used for auto-incrementing integer values. It automatically generates unique identifiers for rows in a table. In MySQL, the equivalent functionality is achieved using AUTO_INCREMENT, which assigns incremental numeric values to a column. Both serve the purpose of creating unique identifiers, albeit with syntactic and implementation differences between the two database systems.

The "clients" table in PostgreSQL is as follows:

SQL

CREATE TABLE clients ( 
id SERIAL,
 full_name VARCHAR,
 address VARCHAR,
 location POINT 
);

The fourth column is present in both PostgresSQL and as well as in MySQL.

Comparing Spatial Data Handling: POINT in PostgreSQL vs MySQL

Spatial data in PostgreSQL and MySQL, particularly the POINT data type, behaves differently. In PostgreSQL, defining a location as a POINT type allows straightforward insertion of spatial data using coordinates.

INSERT INTO clients
(id, full_name, address, location) VALUES 
(3, 'John Alex', '532 Alexander St, WA', POINT
(38.27225, -129.5925));

If we adopted our MySQL schema to match the customers schema from our PostgreSQL database, it would resemble the following:

CREATE TABLE clients
(
    id        INT NOT NULL AUTO_INCREMENT,
    full_name VARCHAR,
    address   VARCHAR,
    location  POINT,
    PRIMARY KEY (id)
);

To transfer the data into our MySQL database, we could execute a query like this:

INSERT INTO clients VALUES (1, 'Jane Cali', '123 Sunny St, AZ', POINT(44.411275716904406,-151.6783709992531));

If we want the actual data coordinates then we use spatial operator functions like ST_asText,

SELECT id, full_name, address, ST_asText(location) FROM clients;

• ST_AsText(location): This function converts the spatial data in the "location" column into its textual representation. It returns the coordinates of the POINT data as a string in the format 'POINT(x y)'.

Now by using the ST_AsText(location), coordinates we get the actual data cordinates.

Handling the UUID Postgres type in MySQL

Handling the UUID PostgreSQL type in MySQL involves several considerations due to their inherent differences:

• Data Type Compatibility: MySQL doesn't have a built-in UUID type like PostgreSQL. You can use CHAR(36) or BINARY(16) to store UUIDs in MySQL.
  
• UUID Generation: In PostgreSQL, UUID generation functions like uuid_generate_v4() are available. In MySQL, you can use the UUID() function or generate UUIDs in your application code.
  
• Indexing: Ensure proper indexing for UUID columns in MySQL to maintain performance, similar to PostgreSQL.
  
• Query Syntax: Adjust queries to match MySQL syntax, especially when dealing with UUID functions or operators.
  
• Migration Considerations: When migrating data from PostgreSQL to MySQL, handle UUID columns appropriately, ensuring compatibility and integrity.
  
• ORM Support: If using an ORM (Object-Relational Mapping) tool, ensure it supports UUID columns in MySQL and handles conversions correctly.
  
• Application Logic: Update application logic to handle UUIDs in MySQL, considering differences in data types and functions.

Database Migration Process

Step 1: Planning and Preparation

Before starting the migration:

• Inventory Assessment: Identify PostgreSQL databases, their size, dependencies, and importance.
  
• Schema Analysis: Understand table structures, indexes, constraints, triggers, and stored procedures.
  
• Compatibility Check: Use tools to ensure compatibility between PostgreSQL and MySQL databases.

Step 2: Schema Conversion

After planning:

• Table Creation: Translate PostgreSQL table definitions to MySQL syntax, ensuring compatibility.
  
• Index and Constraint Conversion: Convert PostgreSQL indexes and constraints to MySQL equivalents.
  
• Stored Procedure Migration: Rewrite PostgreSQL stored procedures, functions, and triggers in MySQL syntax.

Step 3: Data Migration

After schema conversion:

• Export-Import: Transfer data from PostgreSQL to MySQL using pg_dump and import methods like LOAD DATA INFILE or MySQL Workbench.
  
• Third-Party Tools: Utilize services like AWS Database Migration Service (DMS) or open-source tools for automated data migration.

Step 4: Testing and Validation

After data migration:

• Query Validation: Run sample queries on MySQL to verify data consistency and accuracy.
  
• Stored Procedure Testing: Ensure stored procedures, functions, and triggers function correctly in MySQL.
  
• Data Verification: Compare data between PostgreSQL and MySQL databases to validate migration accuracy.

Step 5: Post-Migration Tasks

Following successful testing:

• Backup and Recovery: Secure a backup of the MySQL database for data protection and disaster recovery readiness.
  
• Performance Optimization: Optimize MySQL server settings, indexes, and query execution plans for improved performance.
  
• User Training and Documentation: Educate users on the new MySQL environment and update documentation to reflect database operation changes.

Conclusion

Migrating from PostgreSQL to MySQL demands planning, execution, and validation. Understanding platform differences ensures a smooth transition. Post-migration tasks like backup and training optimize MySQL's performance and ensure seamless operation.