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.
| Metric | PostgreSQL | MySQL |
|---|---|---|
| Licensing | PostgreSQL license (similar to BSD/MIT licenses) | GNU General Public License (source code available) |
| ACID Compliance | Yes | Yes |
| Triggers |
Triggers Support: AFTER, BEFORE, and INSTEAD OF in PostgreSQL |
Supports AFTER and BEFORE triggers |
| Unsigned Integer | No support | Supports unsigned integer columns |
| Materialized Views | Supported | Not by default (PlanetScale Boost provides caching) |
| SQL Compliance | Fully compliant | Mostly compliant |
| Temporary Tables | No TEMP/TEMPORARY keyword | Supports TEMP/TEMPORARY keyword in DROP TABLE |
| Table Partitioning | Supports RANGE, LIST, and HASH methods | Supports various methods including composite keys |
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
);
| id (SERIAL) | name | description | price |
|---|---|---|---|
| 1 | Product A | Description of Product A | 50 |
| 2 | Product B | Description of Product B | 100 |
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
);
| id | full_name | address | location |
|---|---|---|---|
| 1 | John Doe | 123 Main St, Anytown | (40.7128, -74.0060) |
| 2 | Jane Smith | 456 Oak St, Somewhereville | (34.0522, -118.2437) |
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));
| id | full_name | address | location |
|---|---|---|---|
| 1 | John Doe | 123 Main St, Anytown | (40.7128, -74.0060) |
| 2 | Jane Smith | 456 Oak St, Somewhereville | (34.0522, -118.2437) |
|
3 |
John Alex |
532 Alexander St, WA |
(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)’.
| id | full_name | address | location |
|---|---|---|---|
| 1 | Jane Cali | 123 Sunny St, AZ | POINT(44.411275716904406,-151.6783709992531) |
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.