Converting SQL should not begin with changing function names.
It should begin with understanding the query.
Before moving SQL from MySQL to PostgreSQL, SQL Server to Oracle, or between any other database platforms, ask these five questions:
1. What is the query supposed to accomplish?
A query may calculate revenue, identify overdue orders, update customer records, or prepare data for a report.
Understanding its purpose makes it easier to determine whether the converted result still preserves the original business logic.
2. Which parts are specific to the source database?
Look for database-specific elements such as:
• Date and time functions
• String concatenation
• Pagination syntax
• Conditional expressions
• Temporary tables
• Data types
• Stored procedure logic
• Identifier quoting
These are often the areas that require the most attention during conversion.
3. Does the query depend on implicit behavior?
Some databases automatically convert values between data types or handle NULL values differently.
A query that works because of an implicit conversion in one database may fail—or return different results—in another.
SQL that executes successfully is not necessarily SQL that behaves correctly.
4. How will the converted result be validated?
Before conversion, save a representative result from the source database.
After conversion, compare:
• Row counts
• Calculated totals
• NULL values
• Date results
• Sorting behavior
• Duplicate records
Validation should confirm that the meaning of the query survived the migration.
5. Which parts require human review?
Not every SQL construct has a perfect one-to-one equivalent.
Vendor-specific functions, procedural logic, dynamic SQL, and unusual data types may require a developer or database specialist to make the final decision.
A conversion tool should accelerate the work, but review and testing remain essential.
The best SQL migration workflow is not:
Convert → Deploy
It is:
Understand → Convert → Review → Test → Deploy
Sqlinfy helps developers create a strong first-pass conversion across PostgreSQL, SQL Server, MySQL, MariaDB, Oracle, Snowflake, Databricks, and SQLite—while keeping the result available for review.
