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Convert PostgreSQL to MySQL in seconds. Paste Postgres DDL or queries and get clean MySQL syntax, with data types, functions, and operators mapped correctly and every change explained.
PostgreSQL to MySQL is the process of translating database code written in PostgreSQL into equivalent MySQL syntax. A PostgreSQL to MySQL converter rewrites the data types, functions, and operators that differ between the two databases, so a Postgres CREATE TABLE or SELECT statement runs correctly on MySQL without manual edits.
PostgreSQL and MySQL share standard SQL but diverge in their dialects. PostgreSQL uses SERIAL, a native BOOLEAN, the || concatenation operator, and double-quoted identifiers, while MySQL expects AUTO_INCREMENT, TINYINT(1), CONCAT(), and backticks. This converter handles those differences for you.
Converting a Postgres query or schema to MySQL takes only a few seconds and needs no installation. Follow these steps:
Knowing how the two dialects differ explains what the converter changes. PostgreSQL is a feature-rich, standards-leaning database, while MySQL favors simplicity and wide hosting support. The table below sums up the differences that matter most during conversion:
| Aspect | PostgreSQL | MySQL |
|---|---|---|
| Auto-increment key | SERIAL and BIGSERIAL | INT or BIGINT with AUTO_INCREMENT |
| Boolean type | Native BOOLEAN with TRUE and FALSE | TINYINT(1) using 1 and 0 |
| String concatenation | The || operator | The CONCAT() function |
| Identifier quoting | Double quotes around identifiers | Backticks around identifiers |
| Timestamps and JSON | TIMESTAMP, native arrays, and JSONB | DATETIME and JSON, with no array type |
| Pagination | LIMIT with OFFSET | LIMIT with offset, count syntax |
As a tool, the PostgreSQL to MySQL converter offers a few capabilities that make migrating between dialects effortless. Here are the features of our converter:
Converting Postgres to MySQL is useful any time you move workloads, share schemas, or test across databases. The converter speeds up each of these workflows:
This converter is maintained by TestMu AI (formerly LambdaTest), the team behind a unified testing platform, so it is shaped by the same focus on reliable data and schemas that QA engineers depend on. Your query is sent over a secure API only to generate the conversion and is not stored on our servers afterward.
A PostgreSQL to MySQL converter translates code written in PostgreSQL into equivalent MySQL syntax. It rewrites data types, functions, and operators that differ between the two databases, so a Postgres CREATE TABLE or SELECT statement runs correctly on MySQL.
Yes, the PostgreSQL to MySQL converter is free with no signup or login required. You can run up to 20 conversions per day. The tool is maintained by TestMu AI (formerly LambdaTest), the team behind a unified testing platform.
PostgreSQL SERIAL and BIGSERIAL become INT AUTO_INCREMENT and BIGINT AUTO_INCREMENT in MySQL. Because MySQL requires an AUTO_INCREMENT column to be part of a key, the converter keeps it tied to the primary key from your Postgres definition.
PostgreSQL has a native BOOLEAN type with TRUE and FALSE literals. MySQL stores booleans as TINYINT(1) using 1 and 0. The converter maps the BOOLEAN column to TINYINT(1) and rewrites TRUE and FALSE to 1 and 0 where needed.
Yes. Types like arrays and JSONB have no direct MySQL match, so the converter maps arrays to JSON or a comma-separated column and JSONB to MySQL JSON, then notes the change in the explanation so you can adjust the schema if needed.
Yes. Double-quoted PostgreSQL identifiers are rewritten with MySQL backticks, and the Postgres concatenation operator || is converted to the MySQL CONCAT() function, so string expressions behave the same after migration.
Yes. The converter handles DDL such as CREATE TABLE along with SELECT, INSERT, and other statements. It maps column types, default values, and constraints to MySQL so the resulting schema matches your original Postgres structure.
Your query is sent over a secure API call only to generate the conversion and is not stored on our servers. Nothing is saved after the result returns, so you can convert schemas and queries without keeping your SQL on file.
The converter handles the common syntax and type differences accurately, but very database-specific features may need a manual review. Always read the explanation and test the MySQL output against your database before using it in production.
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