Cross-Dialect Schema Migration: MySQL, PostgreSQL, SQL Server and More

Moving a schema from one database engine to another — a cross-dialect schema migration — is harder than a same-engine migration because every dialect has its own type system, syntax, and quirks. This guide covers what translates cleanly, what needs a human, and how to generate correct target-dialect DDL.

What "cross-dialect" actually means

Comparing Postgres to MySQL, or SQL Server to Oracle, is not just a text diff. VARCHAR, SERIAL, AUTO_INCREMENT, IDENTITY, boolean handling, and default expressions all differ. A naive comparison flags equivalent types as changes and produces DDL the target rejects.

What translates cleanly

  • Tables and columns — structural, with type mapping between dialects.
  • Primary and foreign keys — structural; referenced tables are requalified to the target schema.
  • Indexes and unique constraints — translated via each dialect's own CREATE INDEX form.

A good tool is cross-dialect aware: it will not false-flag a Postgres boolean against a MySQL tinyint(1), and it maps types rather than copying them verbatim.

What needs manual review

  • Views and function bodies — these are dialect-specific SQL and are not auto-translated. A cross-dialect view is flagged for manual review with the original body preserved.
  • User-defined types — each engine has its own enum/domain/object model with no clean translation layer.
  • Check constraints and triggers — procedural logic rarely ports one-to-one.

The key is that the tool tells you up front which object types translate cleanly and which need a look, instead of discovering it as a runtime error mid-migration.

Generating the migration

Once you understand the readiness of each object type, generate DDL targeting the destination dialect, review it, and apply it with a snapshot. Treat flagged views, types, and procedural objects as a manual checklist alongside the generated script.

One tool, ten dialects

FoxSchema supports PostgreSQL, MySQL, MariaDB, SQL Server, Azure SQL, Oracle, IBM Db2, SQLite, ClickHouse, and Amazon Redshift, with a cross-dialect readiness panel built in. Download it or read the docs to get started.

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