Vendor Dialects Postgresql Mysql Sql Server Difference

Why this matters

As a Data Analyst, you’ll switch between databases at different companies and tools. Queries that run in PostgreSQL might fail in MySQL or SQL Server due to differences in functions, data types, and syntax. Knowing the key dialect differences helps you ship insights fast instead of debugging tiny syntax issues for hours.

• Build dashboards across tools that use different engines.
• Port shared queries to your company’s main database.
• Review teammates’ SQL from other systems with confidence.

Concept explained simply

SQL is a language standard, but vendors add unique features and slightly different syntax. Think of English spoken in different regions: mostly the same, but with local words and grammar. Your job is to recognize the common core and adjust for each vendor’s accent.

Mental model

• Core: SELECT, FROM, WHERE, GROUP BY, HAVING, JOIN, basic aggregates.
• Dialects differ mainly in: string concatenation, date/time functions, pagination, upserts, identifier quoting, JSON functions, and built-in types.
• Strategy: Write vendor-agnostic logic first. Then swap small syntax pieces (like LIMIT vs TOP) per database.

Quick reference: common differences

Pagination

-- PostgreSQL
SELECT * FROM orders ORDER BY created_at DESC LIMIT 10 OFFSET 20;

-- MySQL
SELECT * FROM orders ORDER BY created_at DESC LIMIT 20, 10;  -- offset, row_count

-- SQL Server
SELECT * FROM orders ORDER BY created_at DESC OFFSET 20 ROWS FETCH NEXT 10 ROWS ONLY;
-- or simple TOP (without offset):
SELECT TOP (10) * FROM orders ORDER BY created_at DESC;

String concatenation

-- PostgreSQL
SELECT 'Hello ' || name;           -- ||
SELECT CONCAT('Hello ', name);     -- treats NULL as empty

-- MySQL
SELECT CONCAT('Hello ', name);     -- NULL in any arg makes result NULL

-- SQL Server
SELECT 'Hello ' + name;            -- NULL + string = NULL
SELECT CONCAT('Hello ', name);     -- treats NULL as empty

Dates and times

-- Current timestamp
-- PostgreSQL: NOW() or CURRENT_TIMESTAMP
SELECT NOW();
-- MySQL: NOW()
SELECT NOW();
-- SQL Server: GETDATE() or SYSDATETIME()
SELECT GETDATE();

-- Add 7 days
-- PostgreSQL
SELECT NOW() + INTERVAL '7 days';
-- MySQL
SELECT DATE_ADD(NOW(), INTERVAL 7 DAY);
-- SQL Server
SELECT DATEADD(DAY, 7, GETDATE());

-- Truncate to month (bucket by month)
-- PostgreSQL
SELECT DATE_TRUNC('month', ts) AS month_bucket FROM t;
-- MySQL (approx via first day of month)
SELECT DATE_FORMAT(ts, '%Y-01-01') = wrong; -- example of a common mistake
-- Correct pattern:
SELECT DATE_FORMAT(ts, '%Y-%m-01') AS month_bucket FROM t;
-- SQL Server
SELECT DATEFROMPARTS(YEAR(ts), MONTH(ts), 1) AS month_bucket FROM t;

Identifier quoting

• PostgreSQL: "CamelCase"
• MySQL: `backticks`
• SQL Server: [brackets] (or " when QUOTED_IDENTIFIER is ON)

Booleans

• PostgreSQL: boolean (TRUE/FALSE)
• MySQL: BOOL is TINYINT(1) alias (use 1/0)
• SQL Server: BIT (1/0/NULL)

Upserts

-- PostgreSQL
INSERT INTO products(id, price) VALUES (1, 9.99)
ON CONFLICT (id) DO UPDATE SET price = EXCLUDED.price;

-- MySQL
INSERT INTO products(id, price) VALUES (1, 9.99)
ON DUPLICATE KEY UPDATE price = VALUES(price);

-- SQL Server (MERGE pattern)
MERGE products AS tgt
USING (SELECT 1 AS id, 9.99 AS price) AS src
ON (tgt.id = src.id)
WHEN MATCHED THEN UPDATE SET price = src.price
WHEN NOT MATCHED THEN INSERT (id, price) VALUES (src.id, src.price);

JSON

-- PostgreSQL
SELECT payload->>'user_id' AS user_id FROM events;   -- text
SELECT payload->'items' AS items_json FROM events;   -- json

-- MySQL
SELECT JSON_EXTRACT(payload, '$.user_id') AS user_id FROM events;

-- SQL Server
SELECT JSON_VALUE(payload, '$.user_id') AS user_id FROM events;
SELECT * FROM OPENJSON(payload, '$.items');

NULL-safe equality

-- PostgreSQL
SELECT a IS NOT DISTINCT FROM b;

-- MySQL
SELECT a <=> b;  -- null-safe equality

-- SQL Server
-- Emulate
SELECT CASE WHEN a = b OR (a IS NULL AND b IS NULL) THEN 1 ELSE 0 END AS equal_null_safe;

String aggregation

-- PostgreSQL
SELECT string_agg(name, ', ') FROM users;

-- MySQL
SELECT GROUP_CONCAT(name ORDER BY name SEPARATOR ', ') FROM users;

-- SQL Server
SELECT STRING_AGG(name, ', ') WITHIN GROUP (ORDER BY name) FROM users;

FULL OUTER JOIN

-- PostgreSQL
SELECT * FROM a FULL OUTER JOIN b USING (id);

-- MySQL (no FULL OUTER JOIN): emulate
SELECT * FROM a LEFT JOIN b USING (id)
UNION ALL
SELECT * FROM a RIGHT JOIN b USING (id)
WHERE a.id IS NULL;

-- SQL Server
SELECT * FROM a FULL OUTER JOIN b ON a.id = b.id;

Worked examples (3 common analyst tasks)

1) Paginate ordered results

Goal: Get the 11–20 most recent orders by created_at.

-- PostgreSQL
SELECT id, created_at
FROM orders
ORDER BY created_at DESC
LIMIT 10 OFFSET 10;

-- MySQL
SELECT id, created_at
FROM orders
ORDER BY created_at DESC
LIMIT 10 OFFSET 10; -- or LIMIT 10, 10

-- SQL Server
SELECT id, created_at
FROM orders
ORDER BY created_at DESC
OFFSET 10 ROWS FETCH NEXT 10 ROWS ONLY;

2) Monthly revenue bucket

Goal: Sum revenue per month from a timestamp column ts.

-- PostgreSQL
SELECT DATE_TRUNC('month', ts) AS month, SUM(amount) AS revenue
FROM payments
GROUP BY 1
ORDER BY 1;

-- MySQL
SELECT DATE_FORMAT(ts, '%Y-%m-01') AS month, SUM(amount) AS revenue
FROM payments
GROUP BY 1
ORDER BY 1;

-- SQL Server
SELECT DATEFROMPARTS(YEAR(ts), MONTH(ts), 1) AS month, SUM(amount) AS revenue
FROM payments
GROUP BY DATEFROMPARTS(YEAR(ts), MONTH(ts), 1)
ORDER BY month;

3) Upsert product price

Goal: Insert price if new, otherwise update.

-- PostgreSQL
INSERT INTO products (id, price)
VALUES (42, 19.99)
ON CONFLICT (id) DO UPDATE SET price = EXCLUDED.price;

-- MySQL
INSERT INTO products (id, price)
VALUES (42, 19.99)
ON DUPLICATE KEY UPDATE price = VALUES(price);

-- SQL Server (MERGE)
MERGE products AS tgt
USING (SELECT 42 AS id, 19.99 AS price) AS src
ON (tgt.id = src.id)
WHEN MATCHED THEN UPDATE SET price = src.price
WHEN NOT MATCHED THEN INSERT (id, price) VALUES (src.id, src.price);

Hands-on exercises

Try these directly in your environment or an online console (per vendor).

• I verified each query runs without syntax errors in my chosen vendor.
• I confirmed null behavior for CONCAT/||/+ and recorded differences.
• I kept the ORDER BY consistent before paginating.

Common mistakes and self-check

• Using LIMIT in SQL Server. Fix: use TOP or OFFSET/FETCH.
• Forgetting ORDER BY before pagination. Self-check: Are pages stable between runs?
• Assuming CONCAT handles NULL the same everywhere. Self-check: Add a NULL case to test.
• Expecting FULL OUTER JOIN in MySQL. Fix: emulate with UNION of LEFT and RIGHT.
• Using wrong identifier quotes. Fix: Postgres ", MySQL `, SQL Server [].
• Mishandling date bucketing. Self-check: Are all timestamps in a month grouped to a single date?

Practical projects

• Build a cross-vendor query notebook: for 10 common tasks (pagination, month buckets, upsert, string_agg, JSON extraction), store the PostgreSQL, MySQL, and SQL Server versions side-by-side.
• Create a portability linter checklist: paste any query and quickly tick through pagination, dates, strings, identifiers, nulls, upserts.
• Migrate a small analytics report (3–5 queries) from one vendor to another; document every change you needed.

Learning path

• First: Master core SQL (SELECT/JOIN/GROUP BY/WHERE/HAVING).
• Then: Learn vendor differences (this lesson).
• Next: Advanced topics per vendor: window functions, CTEs/recursion, JSON, performance basics (indexes, execution order).

Who this is for

• Data Analysts moving between tools or companies.
• Anyone reading/writing queries against multiple databases.
• BI developers maintaining dashboards across engines.

Prerequisites

• Comfort with SELECT, JOINs, GROUP BY, ORDER BY.
• Basic understanding of data types and NULL behavior.

Mini challenge

Write a single analytical task—“Top 5 customers by revenue in the last 30 days”—in all three dialects. Include null-safe concatenation of first and last name as display_name, and make sure pagination/order is deterministic.

Next steps

• Build your own cross-vendor snippet library with comments.
• Practice translating 5–10 queries you already use at work.
• Take the quick test below to cement the differences.

Quick test

Free for everyone. If you log in, your progress and score will be saved automatically.