Why Migrate from MySQL to PostgreSQL?

PostgreSQL has seen explosive growth, becoming the database of choice for many organizations. Common reasons for migration include:

• Advanced Features: Better JSON support, full-text search, and extensibility

• Standards Compliance: Closer adherence to SQL standards

• Complex Queries: Superior handling of CTEs, window functions, and subqueries

• Data Integrity: More robust constraint enforcement

• Licensing: Truly open-source with no commercial restrictions

• Cloud Native: First-class support on all major cloud platforms

MySQL vs PostgreSQL: Key Differences

Syntax Differences

Data Type Mapping

Common Syntax Conversions

1. Table Creation

MySQL:

CREATE TABLE users (
    id INT AUTO_INCREMENT PRIMARY KEY,
    email VARCHAR(255) NOT NULL,
    name VARCHAR(100),
    status ENUM('active', 'inactive', 'pending') DEFAULT 'pending',
    created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
    is_admin TINYINT(1) DEFAULT 0,
    INDEX idx_email (email)
)

PostgreSQL:

CREATE TYPE user_status AS ENUM ('active', 'inactive', 'pending');

CREATE TABLE users (
    id SERIAL PRIMARY KEY,
    email VARCHAR(255) NOT NULL,
    name VARCHAR(100),
    status user_status DEFAULT 'pending',
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    is_admin BOOLEAN DEFAULT FALSE
);

CREATE INDEX idx_email ON users(email)

2. LIMIT and OFFSET

MySQL:

SELECT * FROM products LIMIT 20, 10;  -- Skip 20, get 10

PostgreSQL:

SELECT * FROM products LIMIT 10 OFFSET 20;  -- Same result

3. String Functions

MySQL:

SELECT CONCAT(first_name, ' ', last_name) AS full_name FROM users;
SELECT IFNULL(nickname, username) AS display_name FROM users;
SELECT GROUP_CONCAT(tag SEPARATOR ', ') FROM post_tags GROUP BY

PostgreSQL:

SELECT first_name || ' ' || last_name AS full_name FROM users;
SELECT COALESCE(nickname, username) AS display_name FROM users;
SELECT STRING_AGG(tag, ', ') FROM post_tags GROUP BY

4. Date Functions

MySQL:

SELECT DATE_FORMAT(created_at, '%Y-%m-%d') FROM orders;
SELECT DATE_ADD(order_date, INTERVAL 7 DAY) FROM orders;
SELECT DATEDIFF(end_date, start_date) FROM projects;
SELECT YEAR(created_at), MONTH(created_at) FROM

PostgreSQL:

SELECT TO_CHAR(created_at, 'YYYY-MM-DD') FROM orders;
SELECT order_date + INTERVAL '7 days' FROM orders;
SELECT end_date - start_date FROM projects;  -- Returns interval
SELECT EXTRACT(YEAR FROM created_at), EXTRACT(MONTH FROM created_at) FROM

5. INSERT with Conflict Handling

MySQL:

INSERT INTO users (email, name)
VALUES ('test@example.com', 'Test User')
ON DUPLICATE KEY UPDATE name = VALUES(name)

PostgreSQL:

INSERT INTO users (email, name)
VALUES ('test@example.com', 'Test User')
ON CONFLICT (email) DO UPDATE SET

6. JSON Operations

MySQL:

SELECT JSON_EXTRACT(data, '$.name') FROM profiles;
SELECT * FROM products WHERE JSON_EXTRACT(attributes, '$.color') = 'red'

PostgreSQL:

SELECT data->>'name' FROM profiles;  -- ->> returns text
SELECT * FROM products WHERE attributes->>'color' = 'red';
-- Or with JSONB (recommended):
SELECT * FROM products WHERE attributes @> '{"color": "red"}'

7. Full-Text Search

MySQL:

SELECT * FROM articles
WHERE MATCH(title, content) AGAINST('database optimization' IN NATURAL LANGUAGE MODE)

PostgreSQL:

SELECT * FROM articles
WHERE to_tsvector('english', title || ' ' || content) @@ to_tsquery('database & optimization')

Migration Strategies

Strategy 1: Big Bang Migration

Best for: Small databases, acceptable downtime

1. Put application in maintenance mode

2. Export MySQL data

3. Convert schema

4. Import to PostgreSQL

5. Update application connection strings

6. Test thoroughly

7. Go live

Strategy 2: Parallel Running

Best for: Critical systems, minimal risk tolerance

1. Set up PostgreSQL with converted schema

2. Implement dual-write in application

3. Migrate historical data

4. Run both databases in parallel

5. Validate data consistency

6. Switch reads to PostgreSQL

7. Disable MySQL writes

8. Decommission MySQL

Strategy 3: Incremental Migration

Best for: Large databases, microservices

1. Identify independent data domains

2. Migrate one domain at a time

3. Update relevant services

4. Validate and stabilize

5. Repeat for next domain

Step-by-Step Migration Process

Step 1: Schema Conversion

Option A: Manual Conversion

Review each table and convert syntax manually using the mappings above.

Option B: Automated Tools

Use tools like:

• pgLoader

• AWS DMS (Database Migration Service)

• AI2sql MySQL to PostgreSQL converter

Step 2: Export MySQL Data

# Export schema
mysqldump -u user -p --no-data database_name > schema.sql

# Export data
mysqldump -u user -p --no-create-info

Step 3: Convert Schema

Apply conversions for:

• Data types

• Auto-increment to SERIAL

• ENUM types

• Index syntax

• Engine-specific features

Step 4: Create PostgreSQL Database

createdb -U postgres new_database

# Import converted schema
psql -U postgres -d new_database -f

Step 5: Migrate Data

Using pgLoader (recommended):

Using CSV export/import:

-- MySQL export
SELECT * FROM users INTO OUTFILE '/tmp/users.csv'
FIELDS TERMINATED BY ',' ENCLOSED BY '"' LINES TERMINATED BY '\n';

-- PostgreSQL import
COPY users FROM '/tmp/users.csv' WITH (FORMAT csv, HEADER false)

Step 6: Validate Migration

-- Compare row counts
-- MySQL
SELECT COUNT(*) FROM users;

-- PostgreSQL
SELECT COUNT(*) FROM users;

-- Validate sample data
-- Check specific records match

Step 7: Update Application

Update connection strings:

Before (MySQL):

After (PostgreSQL):

Update ORM/driver configurations for PostgreSQL compatibility.

Common Migration Pitfalls

1. Case Sensitivity

MySQL is case-insensitive by default. PostgreSQL preserves case.

Solution: Standardize to lowercase or use consistent quoting.

2. Zero Dates

MySQL allows '0000-00-00' dates. PostgreSQL does not.

Solution: Convert to NULL or valid dates before migration.

UPDATE orders SET order_date = NULL WHERE order_date = '0000-00-00'

3. Empty Strings vs NULL

MySQL sometimes treats empty strings and NULL differently.

Solution: Audit and standardize before migration.

4. GROUP BY Strictness

PostgreSQL requires all non-aggregated columns in GROUP BY.

MySQL (works):

SELECT name, department, SUM(salary) FROM employees GROUP BY

PostgreSQL (error):

-- Must include name in GROUP BY or use aggregate
SELECT name, department, SUM(salary) FROM employees GROUP BY name,

5. UNSIGNED Integers

PostgreSQL doesn't support UNSIGNED.

Solution: Use appropriate larger type or add CHECK constraint.

CREATE TABLE products (
    id INTEGER PRIMARY KEY CHECK (id >= 0),
    stock INTEGER CHECK (stock >= 0)
)

Using AI2sql for Migration

AI2sql's MySQL to PostgreSQL converter automatically handles:

• Syntax translation

• Data type mapping

• Function conversion

• Index recreation

• Constraint conversion

Example Conversion

Input (MySQL):

SELECT
    IFNULL(u.nickname, u.username) as display_name,
    DATE_FORMAT(o.created_at, '%Y-%m-%d') as order_date,
    GROUP_CONCAT(p.name SEPARATOR ', ') as products
FROM users u
JOIN orders o ON u.id = o.user_id
JOIN order_items oi ON o.id = oi.order_id
JOIN products p ON oi.product_id = p.id
WHERE o.created_at >= DATE_SUB(NOW(), INTERVAL 30 DAY)
GROUP BY u.id
LIMIT 0, 20

Output (PostgreSQL):

SELECT
    COALESCE(u.nickname, u.username) as display_name,
    TO_CHAR(o.created_at, 'YYYY-MM-DD') as order_date,
    STRING_AGG(p.name, ', ') as products
FROM users u
JOIN orders o ON u.id = o.user_id
JOIN order_items oi ON o.id = oi.order_id
JOIN products p ON oi.product_id = p.id
WHERE o.created_at >= NOW() - INTERVAL '30 days'
GROUP BY u.id, u.nickname, u.username
LIMIT 20 OFFSET 0

Conclusion

Migrating from MySQL to PostgreSQL is a significant undertaking, but the benefits often justify the effort. PostgreSQL's advanced features, standards compliance, and robust ecosystem make it an excellent choice for growing applications.

Key takeaways:

1. Plan thoroughly - Document all differences and test conversions

2. Use automated tools - Save time on repetitive conversions

3. Test extensively - Validate data integrity and application behavior

4. Have a rollback plan - Prepare for unexpected issues

5. Leverage AI assistance - Tools like AI2sql accelerate conversion

Need to convert MySQL to PostgreSQL? Try AI2sql's converter - paste your MySQL query and get PostgreSQL syntax instantly.