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SQL is the language people use to define and work with data in relational databases. It lets you create tables, retrieve and change rows, and combine information across tables. The broad ideas are shared, but type names, syntax, and some behaviors vary by database engine—so check the documentation for the specific product and version you use.
What is SQL?
SQL, commonly pronounced “sequel” or spelled out as “S-Q-L,” is a language for working with relational database systems. In a relational database, data is organized into tables: columns describe fields, and rows hold individual records. A database engine implements SQL and defines which features, types, and syntax it supports. PostgreSQL’s PostgreSQL 17 Tutorial introduces SQL alongside relational database concepts; its SQL language reference covers the language’s syntax and facilities.
A SQL statement is an instruction to the database. Depending on the statement, it might define a table, retrieve selected information, add or change records, or manage a group of changes as a transaction.
What are the main categories of SQL commands?
For learning purposes, it is useful to group common statements by their job. These are practical categories, not a guarantee that every database uses identical commands or grammar.
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- Define structures:
CREATE TABLEcreates a table and its columns.ALTER TABLEis commonly used to change a table’s definition. - Read data:
SELECTretrieves rows or calculated expressions from tables and other inputs. - Change data:
INSERTadds rows,UPDATEchanges values in existing rows, andDELETEremoves rows. - Control work: transaction statements let an application commit a set of changes or roll them back, depending on the database and the transaction’s state.
PostgreSQL’s tutorial walks through table creation, populating and querying tables, updates, deletions, and transactions.
What are SQL data types?
A column’s data type describes the kind of value it is intended to hold and how the database interprets that value. Types help make table definitions explicit, but the available names and detailed behavior depend on the engine.
| Value family | Common use | Illustrative type name |
|---|---|---|
| Numeric | Counts, quantities, or measurements | INTEGER |
| Text | Names and other character data | TEXT |
| Date and time | Calendar dates or time-related values | DATE |
| Boolean | True/false values where supported | Engine-specific |
The names in the table are examples, not a cross-database compatibility guarantee. Precision, storage, conversion between types, date/time details, and even whether a type is available can differ. PostgreSQL lists its available types in the PostgreSQL 17 SQL reference; consult the corresponding type documentation for the engine you are using before choosing a type.
A small table definition
This illustrative SQL defines three columns; the type names are not guaranteed to be supported identically by every database.
CREATE TABLE customers (
customer_id INTEGER,
name TEXT,
joined_on DATE
);How do you read a basic SELECT query?
A SELECT query describes the information to return. For example:
SELECT name, joined_on
FROM customers
WHERE joined_on >= DATE '2025-01-01'
ORDER BY joined_on;FROMnames the input table or other source.WHEREfilters individual rows according to a condition.- The select list—
name, joined_onhere—specifies the expressions or columns returned. ORDER BYrequests a particular output order.
The example illustrates common SQL concepts; date literal syntax and supported types can vary, so verify the exact form for your database.
Grouping, duplicates, and missing values
GROUP BYforms groups of rows for aggregate calculations such asCOUNTorAVG.HAVINGfilters groups based on conditions, often involving aggregate results.DISTINCTremoves duplicate result rows. UseORDER BYwhen a particular order matters; removing duplicates is not a substitute for specifying an order.NULLrepresents a missing or unknown value in SQL contexts. It does not behave like an ordinary value in equality comparisons, so check the target engine’s documented operators and rules rather than assuming= NULLworks as an ordinary comparison.
SQLite’s SELECT documentation describes a teaching sequence for a simple query—input, filtering, grouping or result calculation, then duplicate handling—and explicitly treats it as illustrative, not a required physical execution order. That distinction matters: the clauses help you reason about a query, but they do not describe the database’s query plan. SQLite’s expression reference also documents operators and differences from other engines.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What is the difference between INNER JOIN and LEFT JOIN?
A join combines rows from two table-like inputs by pairing them according to a condition. An INNER JOIN returns pairs that satisfy the condition. A LEFT JOIN—also called LEFT OUTER JOIN—returns those matching pairs and also preserves every row from the left input when there is no match; columns from the right input are then filled with NULL.
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| Join form | What it preserves |
|---|---|
INNER JOIN |
Only row pairs satisfying the join condition. |
LEFT JOIN |
All left-side rows, including unmatched ones; unmatched right-side columns are NULL. |
RIGHT JOIN |
All right-side rows, including unmatched ones; unmatched left-side columns are NULL. |
FULL OUTER JOIN |
Matched pairs and unmatched rows from either side, with missing columns set to NULL. |
CROSS JOIN |
Combinations of rows from the inputs, rather than matches selected by a join condition. |
PostgreSQL’s joins tutorial explains pairing rows using a join expression. Its SELECT reference documents join conditions and outer-join results.
Example: keep customers without orders
SELECT customers.name, orders.order_date
FROM customers
LEFT JOIN orders
ON customers.customer_id = orders.customer_id;This query keeps every customer in the result. If a customer has no matching order, the selected orders.order_date value is NULL.
Why ON and WHERE can change an outer join
A frequent source of mistakes is placing a condition on the right-side table in WHERE when the intent is to preserve unmatched left-side rows. An outer join first produces unmatched left rows with NULL values for right-side columns; a later WHERE condition on one of those columns can filter those rows out. SQLite’s SELECT reference explains the distinction between join-condition handling and later filtering. For a query whose unmatched rows must remain, think carefully about whether a condition belongs in ON or WHERE, and verify the target engine’s rules.
Does SQL work the same way in every database?
No. Database products implement SQL with their own supported types, syntax, extensions, and edge-case behavior. A query that is conventional in one engine may need adjustment in another; even familiar areas such as expressions, NULL handling, and join forms deserve version-specific checking. SQLite documents some permissive join forms that it recommends avoiding for portability, while PostgreSQL describes its own supported join forms in its SELECT reference.
Before relying on an example or moving it between systems, check these points:
Quick Recap
- Types: Confirm the required type exists and check its precision, conversion, and date/time semantics.
- Syntax: Prefer explicit, conventional forms such as
JOIN ... ONover permissive shortcuts. - Filtering and NULL: Verify how the engine handles the operators and conditions your query uses.
- Target: Identify the database product and version the code is meant to support, then use that version’s documentation.
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