{"id":3305,"date":"2026-06-02T21:41:52","date_gmt":"2026-06-02T20:41:52","guid":{"rendered":"https:\/\/codeflarelimited.com\/blog\/?p=3305"},"modified":"2026-06-02T21:41:54","modified_gmt":"2026-06-02T20:41:54","slug":"how-to-migrate-from-postgresql-to-mysql","status":"publish","type":"post","link":"https:\/\/codeflarelimited.com\/blog\/how-to-migrate-from-postgresql-to-mysql\/","title":{"rendered":"How To Migrate from PostgreSQL to MySQL"},"content":{"rendered":"\n

Database migration is one of the most challenging tasks in software engineering<\/a>. While both PostgreSQL and MySQL are powerful relational database systems, they differ significantly in SQL syntax, data types, indexing strategies, and advanced features.<\/p>\n\n\n\n

This guide explains how to migrate a PostgreSQL database to MySQL safely, with schema illustrations and practical examples.<\/p>\n\n\n\n

\"Tor<\/a><\/figure>\n\n\n\n

Why Migrate?<\/h2>\n\n\n\n

Organizations migrate from PostgreSQL to MySQL for reasons such as:<\/p>\n\n\n\n

    \n
  • Existing infrastructure already uses MySQL<\/li>\n\n\n\n
  • Lower operational complexity<\/li>\n\n\n\n
  • Team familiarity with MySQL<\/li>\n\n\n\n
  • Hosting provider preferences<\/li>\n\n\n\n
  • Application compatibility requirements<\/li>\n\n\n\n
  • Performance characteristics for specific workloads<\/li>\n<\/ul>\n\n\n\n

    Before You Start<\/h2>\n\n\n\n

    Create a migration inventory:<\/p>\n\n\n\n

    Item<\/th>Description<\/th><\/tr><\/thead>
    Tables<\/td>All database tables<\/td><\/tr>
    Views<\/td>Stored views<\/td><\/tr>
    Indexes<\/td>Primary, unique, composite indexes<\/td><\/tr>
    Constraints<\/td>Foreign keys and checks<\/td><\/tr>
    Functions<\/td>User-defined functions<\/td><\/tr>
    Triggers<\/td>Database triggers<\/td><\/tr>
    Stored Procedures<\/td>Business logic<\/td><\/tr>
    Extensions<\/td>PostgreSQL-specific features<\/td><\/tr>
    Data Volume<\/td>Total records and size<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

    Example:<\/p>\n\n\n\n

    -- PostgreSQL\nSELECT table_name\nFROM information_schema.tables\nWHERE table_schema='public';<\/code><\/pre>\n\n\n\n
    Architecture Overview<\/h3>\n\n\n\n
    Before Migratio<\/p>\n\n\n\n
    After Migration<\/p>\n\n\n\n
    Application\n     \u2502\n     \u25bc\n\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n\u2502 MySQL        \u2502\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518<\/code><\/pre>\n\n\n\n
    Step 1: Analyze PostgreSQL Schema<\/h3>\n\n\n\n
    Example PostgreSQL schema:<\/p>\n\n\n\n
    CREATE TABLE users (\n    id SERIAL PRIMARY KEY,\n    username VARCHAR(100) UNIQUE,\n    email VARCHAR(255),\n    created_at TIMESTAMP DEFAULT NOW()\n);<\/code><\/pre>\n\n\n\n
    Schema Illustration<\/p>\n\n\n\n
    users\n\u251c\u2500\u2500 id (SERIAL)\n\u251c\u2500\u2500 username\n\u251c\u2500\u2500 email\n\u2514\u2500\u2500 created_at<\/code><\/pre>\n\n\n\n
    Step 2: Convert Data Types<\/h3>\n\n\n\n
    One of the biggest migration challenges is data type conversion.<\/p>\n\n\n\n
    Common Mappings<\/h2>\n\n\n\n
    PostgreSQL<\/th>MySQL<\/th><\/tr><\/thead>
    SERIAL<\/td>INT AUTO_INCREMENT<\/td><\/tr>
    BIGSERIAL<\/td>BIGINT AUTO_INCREMENT<\/td><\/tr>
    BOOLEAN<\/td>TINYINT(1)<\/td><\/tr>
    TEXT<\/td>LONGTEXT<\/td><\/tr>
    JSONB<\/td>JSON<\/td><\/tr>
    UUID<\/td>CHAR(36)<\/td><\/tr>
    TIMESTAMP<\/td>TIMESTAMP<\/td><\/tr>
    BYTEA<\/td>BLOB<\/td><\/tr>
    NUMERIC<\/td>DECIMAL<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
    Example<\/h3>\n\n\n\n
    PostgreSQL<\/h3>\n\n\n\n
    CREATE TABLE products (\n    id SERIAL PRIMARY KEY,\n    active BOOLEAN,\n    metadata JSONB\n);<\/code><\/pre>\n\n\n\n
    MySQL<\/h3>\n\n\n\n
    CREATE TABLE products (\n    id INT AUTO_INCREMENT PRIMARY KEY,\n    active TINYINT(1),\n    metadata JSON\n);<\/code><\/pre>\n\n\n\n
    Step 3: Convert Auto Increment Fields<\/h3>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    id SERIAL PRIMARY KEY<\/code><\/pre>\n\n\n\n
    Internally PostgreSQL creates:<\/p>\n\n\n\n
    Sequence\n    \u2502\n    \u25bc\nTable ID<\/code><\/pre>\n\n\n\n
    MySQL uses:<\/p>\n\n\n\n
    id INT AUTO_INCREMENT PRIMARY KEY<\/code><\/pre>\n\n\n\n
    Architecture:<\/p>\n\n\n\n
    Table\n \u2514\u2500\u2500 AUTO_INCREMENT\n       \u2502\n       \u25bc\n  Generates IDs<\/code><\/pre>\n\n\n\n
    Step 4: Convert UUID Columns<\/h3>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    id UUID PRIMARY KEY<\/code><\/pre>\n\n\n\n
    Often generated using:<\/p>\n\n\n\n
    gen_random_uuid()<\/code><\/pre>\n\n\n\n
    MySQL:<\/p>\n\n\n\n
    id CHAR(36) PRIMARY KEY<\/code><\/pre>\n\n\n\n
    Example:<\/p>\n\n\n\n
    INSERT INTO users(id)\nVALUES(UUID());<\/code><\/pre>\n\n\n\n
    Step 5: Convert Boolean Values<\/h3>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    active BOOLEAN<\/code><\/pre>\n\n\n\n
    Values:<\/p>\n\n\n\n
    TRUE\nFALSE<\/code><\/pre>\n\n\n\n
    MySQL:<\/p>\n\n\n\n
    active TINYINT(1)<\/code><\/pre>\n\n\n\n
    Values:<\/p>\n\n\n\n
    1 = TRUE\n0 = FALSE<\/code><\/pre>\n\n\n\n
    Step 6: Convert Date and Time Functions<\/h3>\n\n\n\n
    Current Timestamp<\/h2>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    NOW()<\/code><\/pre>\n\n\n\n
    MySQL:<\/p>\n\n\n\n
    NOW()<\/code><\/pre>\n\n\n\n
    Compatible.<\/p>\n\n\n\n
    Date Difference<\/h3>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    SELECT AGE(NOW(), created_at);<\/code><\/pre>\n\n\n\n
    MySQL:<\/p>\n\n\n\n
    SELECT TIMESTAMPDIFF(DAY, created_at, NOW());<\/code><\/pre>\n\n\n\n
    Date Truncation<\/h2>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    DATE_TRUNC('month', created_at)<\/code><\/pre>\n\n\n\n
    MySQL:<\/p>\n\n\n\n
    DATE_FORMAT(created_at,'%Y-%m-01')<\/code><\/pre>\n\n\n\n
    Step 7: Convert JSON Operations<\/h3>\n\n\n\n
    PostgreSQL is famous for JSONB support.<\/p>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    SELECT metadata->>'name'\nFROM products;<\/code><\/pre>\n\n\n\n
    Example JSON:<\/p>\n\n\n\n
    {\n  \"name\":\"Laptop\",\n  \"price\":500\n}<\/code><\/pre>\n\n\n\n
    MySQL:<\/p>\n\n\n\n
    SELECT JSON_UNQUOTE(\n    JSON_EXTRACT(metadata,'$.name')\n)\nFROM products;<\/code><\/pre>\n\n\n\n
    Step 8: Convert Sequences<\/h3>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    CREATE SEQUENCE invoice_seq;<\/code><\/pre>\n\n\n\n
    Used as:<\/p>\n\n\n\n
    nextval('invoice_seq')<\/code><\/pre>\n\n\n\n
    MySQL has no direct equivalent.<\/p>\n\n\n\n
    Use:<\/p>\n\n\n\n
    AUTO_INCREMENT<\/code><\/pre>\n\n\n\n
    or a custom sequence table:<\/p>\n\n\n\n
    CREATE TABLE sequences (\n    next_id BIGINT\n);<\/code><\/pre>\n\n\n\n
    Step 9: Convert PostgreSQL ENUMs<\/h3>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    CREATE TYPE order_status AS ENUM (\n    'pending',\n    'paid',\n    'cancelled'\n);<\/code><\/pre>\n\n\n\n
    status order_status<\/code><\/pre>\n\n\n\n
    MySQL:<\/p>\n\n\n\n
    status ENUM(\n    'pending',\n    'paid',\n    'cancelled'\n)<\/code><\/pre>\n\n\n\n
    Step 10: Convert Constraints<\/h3>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    ALTER TABLE users\nADD CONSTRAINT email_check\nCHECK (\n    email LIKE '%@%'\n);<\/code><\/pre>\n\n\n\n
    MySQL 8.0 supports CHECK constraints:<\/p>\n\n\n\n
    ALTER TABLE users\nADD CONSTRAINT email_check\nCHECK (\n    email LIKE '%@%'\n);<\/code><\/pre>\n\n\n\n
    For older MySQL versions:<\/p>\n\n\n\n
    Use triggers or application validation.<\/p>\n\n\n\n
    Step 11: Convert Indexes<\/h3>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    CREATE INDEX idx_email\nON users(email);<\/code><\/pre>\n\n\n\n
    MySQL:<\/p>\n\n\n\n
    CREATE INDEX idx_email\nON users(email);<\/code><\/pre>\n\n\n\n
    Mostly identical.<\/p>\n\n\n\n
    Step 12: Convert Full-Text Search<\/h3>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    CREATE INDEX idx_search\nON articles\nUSING GIN(\n    to_tsvector('english',content)\n);<\/code><\/pre>\n\n\n\n
    Search:<\/p>\n\n\n\n
    SELECT *\nFROM articles\nWHERE to_tsvector(content)\n@@ plainto_tsquery('database');<\/code><\/pre>\n\n\n\n
    MySQL:<\/p>\n\n\n\n
    ALTER TABLE articles\nADD FULLTEXT(content);<\/code><\/pre>\n\n\n\n
    Search:<\/p>\n\n\n\n
    SELECT *\nFROM articles\nWHERE MATCH(content)\nAGAINST('database');<\/code><\/pre>\n\n\n\n
    Step 13: Convert Triggers<\/h3>\n\n\n\n
    PostgreSQL:<\/p>\n\n\n\n
    CREATE FUNCTION update_timestamp()\nRETURNS TRIGGER AS $$\nBEGIN\n    NEW.updated_at = NOW();\n    RETURN NEW;\nEND;\n$$ LANGUAGE plpgsql;<\/code><\/pre>\n\n\n\n
    Trigger:<\/p>\n\n\n\n
    CREATE TRIGGER users_update\nBEFORE UPDATE\nON users\nFOR EACH ROW\nEXECUTE FUNCTION update_timestamp();<\/code><\/pre>\n\n\n\n
    MySQL:<\/p>\n\n\n\n
    DELIMITER \/\/\n\nCREATE TRIGGER users_update\nBEFORE UPDATE\nON users\nFOR EACH ROW\nBEGIN\n    SET NEW.updated_at = NOW();\nEND\/\/\n\nDELIMITER ;<\/code><\/pre>\n\n\n\n
    Step 14: Export PostgreSQL Data<\/h3>\n\n\n\n
    Export schema:<\/p>\n\n\n\n
    pg_dump -U postgres \\\n--schema-only \\\nmydb > schema.sql<\/code><\/pre>\n\n\n\n
    Export data:<\/p>\n\n\n\n
    pg_dump -U postgres \\\n--data-only \\\nmydb > data.sql<\/code><\/pre>\n\n\n\n
    Step 15: Transform SQL<\/h3>\n\n\n\n
    Many teams use tools such as:<\/p>\n\n\n\n
      \n
    • pgloader<\/li>\n\n\n\n
    • DBeaver<\/li>\n\n\n\n
    • AWS DMS<\/li>\n\n\n\n
    • Talend<\/li>\n\n\n\n
    • Apache NiFi<\/li>\n<\/ul>\n\n\n\n
      Popular choice:<\/p>\n\n\n\n
      pgloader postgres:\/\/user:pass@host\/db \\\nmysql:\/\/user:pass@host\/db<\/code><\/pre>\n\n\n\n
      Migration Flow:<\/p>\n\n\n\n
      PostgreSQL\n      \u2502\n      \u25bc\n   pgloader\n      \u2502\n      \u25bc\n    MySQL<\/code><\/pre>\n\n\n\n
      Step 16: Import into MySQL<\/h3>\n\n\n\n
      Create database:<\/p>\n\n\n\n
      CREATE DATABASE appdb;<\/code><\/pre>\n\n\n\n
      Import:<\/p>\n\n\n\n
      mysql -u root -p appdb < schema.sql\nmysql -u root -p appdb < data.sql<\/code><\/pre>\n\n\n\n
      Step 17: Verify Data Integrity<\/h3>\n\n\n\n
      Compare row counts.<\/p>\n\n\n\n
      PostgreSQL:<\/p>\n\n\n\n
      SELECT COUNT(*)\nFROM users;<\/code><\/pre>\n\n\n\n
      MySQL:<\/p>\n\n\n\n
      SELECT COUNT(*)\nFROM users;<\/code><\/pre>\n\n\n\n
      Compare:<\/p>\n\n\n\n
      PostgreSQL = 150,000 rows\nMySQL      = 150,000 rows<\/code><\/pre>\n\n\n\n
      Check:<\/p>\n\n\n\n
        \n
      • Foreign keys<\/li>\n\n\n\n
      • Null values<\/li>\n\n\n\n
      • UUIDs<\/li>\n\n\n\n
      • JSON fields<\/li>\n\n\n\n
      • Dates<\/li>\n\n\n\n
      • Monetary values<\/li>\n<\/ul>\n\n\n\n
        Step 18: Application Changes<\/h3>\n\n\n\n
        Update connection strings.<\/p>\n\n\n\n
        PostgreSQL:<\/p>\n\n\n\n
        DATABASE_URL=postgres:\/\/user:password@localhost\/app<\/code><\/pre>\n\n\n\n
        MySQL:<\/p>\n\n\n\n
        DATABASE_URL=mysql:\/\/user:password@localhost\/app<\/code><\/pre>\n\n\n\n
        Example Node.js connection:<\/p>\n\n\n\n
        \/\/ PostgreSQL\nconst { Pool } = require('pg');<\/code><\/pre>\n\n\n\n
        becomes<\/p>\n\n\n\n
        \/\/ MySQL\nconst mysql = require('mysql2');<\/code><\/pre>\n\n\n\n
        Common Problems and Solutions<\/h2>\n\n\n\n
        Problem<\/th>Solution<\/th><\/tr><\/thead>
        SERIAL not working<\/td>Replace with AUTO_INCREMENT<\/td><\/tr>
        JSONB operators fail<\/td>Use JSON_EXTRACT<\/td><\/tr>
        UUID generation missing<\/td>Use UUID()<\/td><\/tr>
        Sequences unavailable<\/td>Use AUTO_INCREMENT<\/td><\/tr>
        GIN indexes unsupported<\/td>Use FULLTEXT indexes<\/td><\/tr>
        PL\/pgSQL functions fail<\/td>Rewrite as MySQL procedures<\/td><\/tr>
        Array columns unsupported<\/td>Normalize tables or use JSON<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
        Example Complete Conversion<\/h1>\n\n\n\n
        PostgreSQL<\/h3>\n\n\n\n
        CREATE TABLE orders (\n    id SERIAL PRIMARY KEY,\n    customer_id UUID,\n    amount NUMERIC(10,2),\n    metadata JSONB,\n    created_at TIMESTAMP DEFAULT NOW()\n);<\/code><\/pre>\n\n\n\n
        MySQL<\/h3>\n\n\n\n
        CREATE TABLE orders (\n    id INT AUTO_INCREMENT PRIMARY KEY,\n    customer_id CHAR(36),\n    amount DECIMAL(10,2),\n    metadata JSON,\n    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP\n);<\/code><\/pre>\n\n\n\n
        Schema Illustration<\/p>\n\n\n\n
        orders\n\u251c\u2500\u2500 id\n\u2502    \u2514\u2500\u2500 AUTO_INCREMENT\n\u251c\u2500\u2500 customer_id\n\u251c\u2500\u2500 amount\n\u251c\u2500\u2500 metadata\n\u2514\u2500\u2500 created_at<\/code><\/pre>\n\n\n\n
        Recommended Migration Workflow<\/h1>\n\n\n\n
        1. Backup PostgreSQL\n          \u2502\n          \u25bc\n2. Analyze Schema\n          \u2502\n          \u25bc\n3. Convert Data Types\n          \u2502\n          \u25bc\n4. Convert Functions\n          \u2502\n          \u25bc\n5. Convert Triggers\n          \u2502\n          \u25bc\n6. Migrate Data\n          \u2502\n          \u25bc\n7. Verify Integrity\n          \u2502\n          \u25bc\n8. Update Application\n          \u2502\n          \u25bc\n9. Performance Testing\n          \u2502\n          \u25bc\n10. Production Cutover\n<\/code><\/pre>\n\n\n\n
        For large production databases (millions of records), tools such as pgloader<\/strong>, AWS Database Migration Service (DMS)<\/strong>, or dual-write replication strategies<\/strong> are generally safer than exporting SQL dumps manually, because they can handle schema conversion, large datasets, and minimal downtime more effectively.<\/p>\n","protected":false},"excerpt":{"rendered":"
        Database migration is one of the most challenging tasks in software engineering. While both PostgreSQL and MySQL are<\/p>\n","protected":false},"author":1,"featured_media":3306,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[98],"tags":[],"class_list":["post-3305","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-softare-development"],"yoast_head":"\nHow To Migrate from PostgreSQL to MySQL<\/title>\n<meta name=\"description\" content=\"Database migration is one of the most challenging tasks in software engineering. 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