In SQL, there is no specific data type called “float”. However, SQL provides several numeric data types that can be used to store floating-point numbers. These data types include **REAL**, **DOUBLE PRECISION**, and **NUMERIC**.

## REAL Data Type:

The __REAL__ data type is used to store single-precision floating-point numbers in SQL. It can represent values with a precision of approximately 6 decimal places. The syntax for defining a column with the REAL data type is as follows:

```
CREATE TABLE my_table (
my_column REAL
);
```

## DOUBLE PRECISION Data Type:

The __DOUBLE PRECISION__ data type is used to store double-precision floating-point numbers in SQL. It can represent values with a precision of approximately 15 decimal places. The syntax for defining a column with the DOUBLE PRECISION data type is as follows:

```
CREATE TABLE my_table (
my_column DOUBLE PRECISION
);
```

## NUMERIC Data Type:

The __NUMERIC__ data type, also known as __DECIMAL__, can be used to store fixed-point or variable precision numbers in SQL. It allows you to specify the precision (total number of digits) and scale (number of digits after the decimal point). The syntax for defining a column with the NUMERIC data type is as follows:

```
CREATE TABLE my_table (
my_column NUMERIC(precision, scale)
);
```

**Note:**

- The precision and scale values in the NUMERIC data type determine the maximum range and precision of the numbers that can be stored in the column.
- The REAL and DOUBLE PRECISION data types are approximate numeric data types, while the NUMERIC data type is exact.

## Example:

Let’s consider an example where we want to store the average temperature readings in a weather database. We can define a table with a column of type DOUBLE PRECISION as follows:

```
CREATE TABLE weather_data (
temperature DOUBLE PRECISION
);
```

In this example, the temperature column will be able to store floating-point numbers with a precision of approximately 15 decimal places.

## Conclusion:

In SQL, there is no specific float data type. However, you can use the REAL, DOUBLE PRECISION, or NUMERIC data types to store floating-point numbers with different levels of precision. Choose the appropriate data type based on your requirements for precision and scale.

By understanding these different numeric data types in SQL, you can ensure accurate storage and manipulation of floating-point numbers in your database.