Why MySQL to PostgreSQL converters fail and how to migrate correctly

Migrating between relational databases is rarely as straightforward as it sounds. When engineers attempt to switch from MySQL to PostgreSQL—or vice versa—they often discover that tools promising seamless conversion fall short at the first major hurdle. These utilities typically rely on basic pattern matching or regex to rewrite SQL syntax, a method that overlooks nuanced differences in data handling, constraints, and engine behaviors. The result? Silent failures that only surface after migration, when critical data integrity issues emerge in production.

The limitations of text-based migration tools

Most open-source or commercial MySQL-to-PostgreSQL converters operate on a fundamental assumption: SQL is just text that can be transformed with find-and-replace logic. This approach works for simple queries but collapses under real-world complexity. Consider these common edge cases that derail migrations:

• Invalid zero dates: MySQL allows 0000-00-00 as a default date, but PostgreSQL rejects it outright, causing import failures.
• AUTO_INCREMENT gaps: MySQL sequences must be converted to PostgreSQL sequences with counters aligned to existing data.
• ENUM types skipped: Many tools either ignore ENUM columns or flatten them into VARCHAR, losing application logic tied to specific values.
• Quote confusion: Mixed use of backticks (MySQL) and double quotes (PostgreSQL) can silently corrupt identifiers during parsing.
• Encoding mismatches: Latin1-encoded columns containing emoji or special characters often get mangled when charset assumptions are violated.

These issues typically surface only after migration, when developers realize data is missing, corrupted, or non-functional in the new system. By then, the rollback process is costly and disruptive.

A robust alternative: engine-level conversion

Rather than treating SQL as pure text, a more reliable approach loads the database schema directly from the live engine. This method avoids text parsing entirely and instead extracts metadata—tables, columns, constraints, and sequences—in their native formats. The process unfolds in three steps:

1. Load the dump into a sandboxed database (MySQL 8.0 or PostgreSQL 16 instance) to avoid affecting production systems.
2. Convert schema and data programmatically by reading the actual catalog, not the SQL dump text.
3. Export clean, validated SQL from the target engine, ensuring compatibility with the destination system.

This engine-level strategy guarantees that the output SQL is syntactically correct for the target database because it originates from a real database instance. The conversion accounts for engine-specific behaviors, data types, and constraints—without relying on brittle text manipulation.

The overlooked challenge: PostgreSQL to MySQL migration

Most migration tools focus only on MySQL-to-PostgreSQL conversions, leaving PostgreSQL-to-MySQL migrations underserved. Yet, the reverse direction introduces its own set of hurdles, primarily due to PostgreSQL’s richer type system and advanced features. These include:

• UUID support: PostgreSQL’s uuid type must map to MySQL’s CHAR(36), with defaults like gen_random_uuid() converted to (uuid()).
• JSON and binary JSON: PostgreSQL’s jsonb requires conversion to MySQL’s JSON, with query functions adjusted accordingly.
• Array types: PostgreSQL arrays become JSON arrays in MySQL, requiring transformation logic during export.
• Timestamp precision: PostgreSQL’s timestamptz with microsecond precision must convert to MySQL’s DATETIME(6), preserving timezone awareness.
• Identity and sequence handling: PostgreSQL’s IDENTITY or SERIAL columns need to map to MySQL’s AUTO_INCREMENT, with counters aligned to existing data.

Solutions like SwapSQL handle these conversions natively, validating the output by loading it into a real MySQL instance before delivery. This ensures that the generated SQL is not just syntactically correct but also functionally compatible.

Free, no-account migrations up to 10 MB

For teams testing migration workflows or handling smaller datasets, some services offer a free tier with generous limits. Dumps up to 10 MB convert without account creation, and compressed .sql.gz files are accepted—effectively supporting raw SQL files up to 100 MB. This reduces friction for developers exploring migration options without committing to enterprise-grade tools.

Database migration doesn’t have to be a gamble. By moving beyond text-based parsing and leveraging engine-level conversion, teams can avoid hidden pitfalls and ensure data integrity during transitions between MySQL and PostgreSQL.