SQL INSERT Statement -

SQL INSERT Statement

The SQL INSERT statement is a fundamental tool in a database developer’s arsenal, enabling the addition of new data with precision and control. By understanding its syntax and use cases, developers can harness the full power of this statement to maintain data accuracy and efficiency in their relational databases.

The SQL INSERT statement is used to add new records (rows) to a table in a relational database. It allows you to specify the values for each column when inserting data into a table.

In the below PDF we discuss about SQL INSERT Statement in detail in simple language, Hope this will help in better understanding.

Understanding the Basics:

The SQL INSERT statement is employed to insert new rows into a table. The basic Syntax looks like this:

INSERT INTO table_name (column1, column2, column3, ...)
VALUES (value1, value2, value3, ...);

table_name: the name of the table where the data will be inserted.
(column1, column2, column3, …): the columns in the table to which data will be added.
VALUES (value1, value2, value3, …): the values to be inserted into the specified columns.
Example:

INSERT INTO employees (employee_id, first_name, last_name, salary)
VALUES (101, 'John', 'Doe', 50000);

Common Use Cases:

1. Inserting Data into Specific Columns:
You can specify the columns into which you want to insert data. This is especially useful when the table has many columns, and you only want to provide values for a subset of them.

INSERT INTO products (product_id, product_name)
VALUES (1, 'Laptop');

2. Inserting Data into All Columns:
If you’re inserting values into all columns, you can omit the column names. However, ensure that the order of values matches the order of columns in the table.

INSERT INTO customers
VALUES (101, 'Alice', 'Johnson', 'alice@email.com');

3. Inserting Multiple Rows at Once:
The INSERT statement can be used to insert multiple rows in a single query, reducing the number of round-trips to the database.

INSERT INTO orders (order_id, customer_id, order_date)
VALUES (1, 101, '2024-01-09'),
(2, 102, '2024-01-10'),
(3, 103, '2024-01-11');