The difference between null and empty in sql

NULL in SQL represents an unknown or non-existent value. It has its own data type and cannot be indexed. It usually takes up less storage space and is FALSE in Boolean expressions; null represents an empty string and has String data type, can be indexed, is treated as TRUE. Use NULL to indicate that the data is unknown, and use NULL to indicate that the data is an empty string.

The difference between NULL and empty in SQL

What is NULL?

NULL represents an unknown or non-existent value in SQL. It is not an empty string, 0, or any other value, but is used specifically to indicate missing data.

What is empty?

Empty means a string containing a zero-length string or no characters. It is not NULL because it contains a value, although the value is empty.

Key Differences

• Data Types: NULL has its own data type called UNKNOWN. Empty has the string data type.
• Comparison: NULL always returns NULL when compared to any value, including NULL. Null can be compared with other null values ​​and returns TRUE.
• Index: NULL values ​​cannot be indexed. Null values ​​can be indexed.
• Storage space: NULL usually takes up less storage space than the null value because it does not need to store the actual value.
• Logical values: NULL is treated as FALSE in Boolean expressions. Empty is considered TRUE.

When to use NULL and empty?

• Use NULL: When the data is completely unknown or does not exist.
• Use empty: When the data is an empty string or contains meaningless values.

Example

• NULL: A customer's address field may be NULL because the customer has not yet provided an address.
• Empty: The description field of a product may be empty because the product has no description.

Note:

There are subtle differences between some SQL dialects (e.g. MySQL) for NULL and empty. However, the key differences described above generally apply to most SQL implementations.

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