MySQL vs PostgreSQL vs T-SQL: Which SQL Should You Learn First?
MySQL, PostgreSQL, T-SQL: which one should you learn? Pick PostgreSQL and stop worrying. Around 90% of what you learn transfers to every other database. The remaining 10% is small syntax differences you can look up in an afternoon when a job needs them.
This is one of the most common beginner worries, and it's understandable: when you search "learn SQL," you immediately run into a list of products with different names. Here's what those names actually mean, what's different between them, and why the choice matters much less than it looks.
SQL Is a Language. These Are Databases.
SQL (Structured Query Language) is a standard language for working with relational databases. MySQL, PostgreSQL, SQL Server, SQLite, Oracle, Snowflake and BigQuery are database products that all speak SQL.
Each product adds its own extras and has a few quirks, which people call its dialect. T-SQL is the name of Microsoft SQL Server's dialect. PL/pgSQL and PL/SQL are procedural extensions for PostgreSQL and Oracle, used for writing stored procedures (which, as an analyst, you'll rarely need).
A useful comparison: they're like regional accents of English. Someone from London and someone from Texas use a few different words, but they understand each other fine.
What's Exactly the Same Everywhere
Everything that matters most for learning works identically, or nearly so, in every major database:
SELECT c.name, COUNT(o.id) AS orders, SUM(o.amount) AS revenue
FROM customers c
LEFT JOIN orders o ON o.customer_id = c.id
WHERE c.country = 'Canada'
GROUP BY c.name
HAVING COUNT(o.id) > 2
ORDER BY revenue DESC;That query runs unchanged in PostgreSQL, MySQL, SQL Server, SQLite, Snowflake and BigQuery (BigQuery just needs its dataset-qualified table names). The same goes for:
- SELECT, WHERE, ORDER BY
- All JOIN types (except one MySQL gap, below)
- GROUP BY, HAVING and aggregate functions
- CASE WHEN, COALESCE, IN, BETWEEN, LIKE
- Subqueries and CTEs (
WITH) - Window functions (
ROW_NUMBER,RANK,LAG, running sums)
In other words: every concept in a typical SQL interview.
What's Actually Different
The differences are mostly small syntax details. Here are the ones beginners run into first:
| Task | PostgreSQL | MySQL | SQL Server (T-SQL) |
|---|---|---|---|
| First 10 rows | LIMIT 10 | LIMIT 10 | SELECT TOP 10 ... |
| Join strings | a || b or CONCAT() | CONCAT(a, b) | a + b or CONCAT() |
| Current time | NOW() | NOW() | GETDATE() |
| Replace NULL | COALESCE() | COALESCE() or IFNULL() | COALESCE() or ISNULL() |
| Days between dates | d2 - d1 | DATEDIFF(d2, d1) | DATEDIFF(day, d1, d2) |
| Truncate to month | DATE_TRUNC('month', d) | DATE_FORMAT(d, '%Y-%m-01') | DATETRUNC(month, d) (2022+) |
| Case-insensitive match | ILIKE | LIKE (usually case-insensitive by default) | LIKE (depends on collation) |
| FULL OUTER JOIN | Yes | No (use LEFT + RIGHT with UNION) | Yes |
That's most of it. If you know how to write a query in one dialect, switching is a matter of searching "datediff in SQL Server" the first few times and then remembering it.
Employers hiring analysts test whether you can think in SQL. Nobody fails an interview because they wrote LIMIT instead of TOP.
So Which Should You Learn?
The default: PostgreSQL
For most beginners, and especially aspiring data analysts, PostgreSQL is the best starting point:
- It follows the SQL standard closely, so what you learn transfers cleanly to other databases.
- It has the most complete feature set of the free databases: full window function support, FULL OUTER JOIN, excellent date handling, and
FILTERclauses for conditional aggregation. - It's free and runs everywhere, including free cloud tiers and Docker.
- Modern analytics warehouses feel familiar after it. Snowflake, Redshift and DuckDB syntax is close to PostgreSQL's, and Redshift is directly derived from it.
When MySQL makes sense
MySQL is a perfectly good choice if a course you like uses it, or if you're heading toward web development. A huge number of websites run on it. Just make sure you're using MySQL 8 or newer; older versions lack window functions and CTEs, which are essential for analyst work.
When SQL Server makes sense
If you're applying to companies in a Microsoft-heavy environment (lots of Excel, Power BI and Azure, common in finance, healthcare and government), job listings may mention SQL Server or T-SQL. In that case, learning in SQL Server makes sense. It's still the same skills.
Check your target job listings
The most reliable tiebreaker: search 20 analyst job listings in your area and note which databases they mention. Many will just say "SQL." Many mention a cloud warehouse (Snowflake, BigQuery, Redshift) that you can't easily install at home anyway, and where the PostgreSQL-style syntax you already know will carry over.
What About the YouTube Recommendation?
Beginners also often ask which YouTube course to follow. Rather than pointing to one channel, the advice that matters more: whatever you pick, don't just watch. Pause every few minutes and write the query yourself before the instructor does. Watching someone else write SQL feels productive, but almost all the learning happens when you type it, break it and fix it yourself.
Skip the Setup and Start Writing Queries
If installing a database is what's stopping you, you don't need to do it today. SQL Side Quest's Learning Mode runs real PostgreSQL queries from your browser with no install and no account. Learn the language first; pick your local setup later.