SQL Dialect Differences: Translate Queries Without Changing Their Meaning

A syntax difference is visible when an engine rejects LIMIT or a particular identity declaration. A semantic difference is visible when an accepted CAST or sort produces a different result. Translation needs both checks. State the intended record population, output grain, NULL policy and numeric precision before selecting local syntax.

Keep dialect-specific fragments small and labelled in application code or documentation. A generic abstraction can help, but it cannot remove every database difference. Automated tests should include unknown values, ties and invalid import strings, because ordinary happy-path rows can make non-equivalent queries appear identical. Compare typed values rather than only screenshots whose decimal formatting differs by client.

Use single quotes for ordinary string literals. Identifier quotes differ: PostgreSQL uses double quotes, MySQL commonly uses backticks, and SQL Server often uses brackets. MySQL SQL modes can change double-quote interpretation. Simple names that avoid spaces and reserved keywords reduce the need for quoting without eliminating every case-sensitivity consideration.

Generated keys use AUTO_INCREMENT in MySQL, identity declarations in PostgreSQL, IDENTITY in SQL Server and special INTEGER PRIMARY KEY behaviour in SQLite. These mechanisms allocate keys but do not promise gap-free business numbers. PostgreSQL and SQL Server schemas are namespaces inside databases; MySQL uses database and schema in closely corresponding ways; SQLite commonly uses database files and attachment names.

PostgreSQL, MySQL and SQLite commonly use LIMIT after ORDER BY. SQL Server uses TOP near SELECT or OFFSET/FETCH with ordering. PostgreSQL also supports standard-style FETCH FIRST. Translate the whole ordering contract, including unique tie-breakers, rather than merely replacing the limit keyword. A first page chosen from an unspecified order has no dependable business meaning.

Default NULL placement differs between PostgreSQL and the other three in ordinary ascending sorts. CASE WHEN value IS NULL THEN 1 ELSE 0 END provides an explicit portable missing-last key. PostgreSQL and SQLite also accept NULLS LAST syntax, but MySQL and SQL Server do not share that form. Collation affects text order separately from missing-value placement.

Exact decimal arithmetic in server engines is not reproduced by merely declaring DECIMAL in ordinary SQLite. SQLite uses affinity and storage classes, while STRICT tables impose stronger rules with a restricted type-name set. Boolean, JSON and timestamp declarations also need deliberate local choices. A migration should map domain requirements, not only copy the source type’s spelling.

CAST has a shared standard-style syntax, but invalid-text behaviour and target types differ. SQL Server CONVERT has a type-first form and optional styles; MySQL CONVERT uses different forms. Integer division and AVG result types can affect fractions. Use appropriate decimal operands and test zero denominators, unknown inputs and rounding boundaries in every target engine.

Temporal part extraction and arithmetic have different function families: EXTRACT and intervals in PostgreSQL, DATE_ADD and related functions in MySQL, DATEPART and DATEADD in SQL Server, and date modifiers or strftime in SQLite. Define whether the field is a date, a local timestamp or an instant before translating a function. A half-open range is a useful shared period-filter pattern.

MySQL has no native FULL OUTER JOIN. Modern SQLite supports RIGHT and FULL joins from version 3.39, while older installations need alternatives. SQLite does not implement quantified ANY and ALL subquery comparisons. PostgreSQL and SQLite aggregate FILTER syntax is not shared by MySQL and SQL Server; CASE inside an aggregate is a portable fixed-category alternative.

Database creation is server administration in MySQL, PostgreSQL and SQL Server, while SQLite opens files or in-memory connections. DDL rollback behaviour differs: many MySQL DDL commands cause implicit commits, whereas PostgreSQL can roll back many table changes. A migration framework must use the target engine’s actual operation rules rather than assuming every statement is transactional.

Unique-constraint NULL handling differs, and SQLite foreign-key enforcement must normally be enabled per connection. CTEs and windows require sufficiently modern versions; MySQL INTERSECT and EXCEPT support begins in 8.0.31. Document a minimum supported version and verify the deployed library or server, especially when SQLite is bundled inside an application and differs from the developer’s command-line tool.

These four readings contain positive, zero, negative and unknown measurements. The simple table supports a shared read example. In SQLite the DECIMAL declaration does not provide the same exact numeric enforcement as a fixed-decimal column in the server databases.

CREATE TABLE dialect_readings (id INTEGER PRIMARY KEY,label VARCHAR(20) NOT NULL,value DECIMAL(10,2));
INSERT INTO dialect_readings (id,label,value) VALUES
 (1,'North',15),(2,'South',NULL),(3,'East',0),(4,'West',-3);

Count all readings, count known measurements and calculate their known sum using shared aggregate syntax.

SELECT COUNT(*) AS all_rows,COUNT(value) AS known_values,SUM(value) AS known_total
FROM dialect_readings;

all_rows | known_values | known_total
4 | 3 | 12

Four records exist, three measurements are known, and fifteen plus zero minus three gives twelve. The zero is a known measurement and must remain in the known-value count. The unknown value is skipped by the expression count and sum. Compare these numerical values across engines while allowing clients to display decimal scale differently; formatting differences alone are not semantic failures.

The PostgreSQL SELECT reference, MySQL SELECT reference, SQL Server SELECT reference and SQLite SELECT reference define their respective query forms.