SQL Commands that every Developer should know

SQL (Structured Query Language) is a powerful language used for managing and manipulating relational databases. Here are some essential SQL commands that every developer should be familiar with:

SELECT: Retrieves data from one or more tables.

 SELECT column1, column2 FROM table_name WHERE condition;

INSERT: Adds new records to a table.

 INSERT INTO table_name (column1, column2) VALUES (value1, value2);

UPDATE: Modifies existing records in a table.

 UPDATE table_name SET column1 = value1 WHERE condition;

DELETE: Removes records from a table.

 DELETE FROM table_name WHERE condition;

CREATE TABLE: Creates a new table with specified columns and data types.

 CREATE TABLE table_name (
     column1 datatype,
     column2 datatype,
     ...
 );

ALTER TABLE: Modifies an existing table (e.g., add, modify, or drop columns).

 ALTER TABLE table_name
 ADD column_name datatype;

 ALTER TABLE table_name
 MODIFY column_name datatype;

 ALTER TABLE table_name
 DROP COLUMN column_name;

DROP TABLE: Deletes an existing table and its data.
```
 DROP TABLE table_name;
```
CREATE INDEX: Creates an index on one or more columns to improve query performance.
```
 CREATE INDEX index_name
 ON table_name (column1, column2, ...);
```

UNION: Combines the result sets of two or more SELECT statements.

 SELECT column1, column2 FROM table1
 UNION
 SELECT column1, column2 FROM table2;

JOIN: Retrieves data from multiple tables based on a related column.

SELECT column1, column2
FROM table1
INNER JOIN table2 ON table1.column = table2.column;

GROUP BY: Groups rows based on the values in specified columns.

SELECT column1, COUNT(*)
FROM table_name
GROUP BY column1;

HAVING: Filters the results of a GROUP BY query.

SELECT column1, COUNT(*)
FROM table_name
GROUP BY column1
HAVING COUNT(*) > 1;

These are fundamental SQL commands, and mastering them will provide a solid foundation for working with relational databases. Depending on the specific database system you're using (e.g., MySQL, PostgreSQL, SQL Server), there may be some variations in syntax and additional features.