Usage of varchar and numeric in sql

VARCHAR is used to store variable-length strings (1-8000 characters), and NUMERIC is used to store precise numbers (specified length and precision). The difference between the two lies in length, data type, precision and storage space. The length of VARCHAR is variable, and the length of NUMERIC is fixed; VARCHAR stores strings, and NUMERIC stores numbers; NUMERIC has higher precision; VARCHAR only stores the necessary length, and NUMERIC always occupies the specified length.

Usage of VARCHAR and NUMERIC in SQL

VARCHAR

VARCHAR is a variable-length data type used to store variable-length string data. Its length can be specified when defining the data type and ranges from 1 to 8,000 characters. VARCHAR is typically used to store text, addresses, or any other data that may require varying lengths.

NUMERIC

NUMERIC is a fixed-length data type used to store precise definite numbers. Its length and precision can be specified when defining the data type. Length refers to the total number of digits in the numeric part, while precision refers to the number of digits after the decimal point. NUMERIC is typically used to store monetary values, measurements, or any other data that requires a precise numerical representation.

The difference between VARCHAR and NUMERIC

• Length: The length of VARCHAR is variable, while the length of NUMERIC is fixed.
• Data type: VARCHAR stores string data, while NUMERIC stores numeric data.
• Precision: NUMERIC provides higher precision, while VARCHAR has no precision.
• Storage space: VARCHAR only stores data of the necessary length, while NUMERIC always occupies its specified length.

USE CASE

• VARCHAR:

  • Store user name
  • Storage address
  • Storage product description

• NUMERIC:

  • Storage currency amount
  • Storing distance measurements
  • Storing scientific calculation results

Notes

• VARCHAR stores string data, so mathematical operations are not possible.
• NUMERIC stores precise definites and is therefore not suitable for approximate calculations.
• When choosing a data type, carefully consider the size, precision, and usage of the data.

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