Which of the following is a valid SQL type

Which of the following is a valid SQL type

A) CHARACTER
B) NUMERIC 
C) FLOAT 
D) All the above

The correct answer to the question ” Which of the following is a valid SQL type?” is option (D) ALL THE ABOVE

Explanation: ‘CHARACTER’, ‘NUMERIC’, and ‘FLOAT’ all are valid SQL types.

Table of contents:

Let’s have a clear and detailed look at every option

SQL Valid Data Types 

Option A: CHARACTER in SQL

CHARACTER is a valid SQL type according to the SQL standard, but CHAR is the preferred and more widely used term. The purpose of CHAR(or CHARACTER) data type in SQL is to store fixed-length character strings. It is used for strings where the length of the text is always the same. 

How does the CHARACTER Data type work in SQL?

If the string is shorter than the specified length, it will be padded with spaces. For example, if you define a column as CHAR(10) and store a 5-character string, the database will pad it with 5 spaces to make it 10 characters in length.

If you store a string of exactly 10 characters, then it will be stored without padding.

Example :

CREATE TABLE example (
    code CHAR(5)  
);

This SQL statement creates a table named example with a column called “code” that stores fixed-length strings of exactly 5 characters.

Option B: NUMERIC in SQL

The NUMERIC type is used for exact numeric values with a specified accuracy and scale. It’s commonly used for financial data, values, and other applications where accuracy is crucial.  It is similar to DECIMAL.

It is defined as NUMERIC(p, s) where :

  • p(precision or accuracy) is the total number of digits the number can have both to the left and right of the decimal point.
  • s(scale) number of digits allowed after the decimal point

Example : 

Creating a SQL Table bank_accounts

CREATE TABLE bank_accounts (
    account_id SERIAL PRIMARY KEY,
    account_holder VARCHAR(100),
    balance NUMERIC(15,2)
);

Inserting values in the bank_accounts Table

INSERT INTO bank_accounts (account_holder, balance)

VALUES ('Alice', 1000.50),
       ('Bob', 2500.75),
       ('Charlie', 1500.25);

The SQL INSERT INTO statement adds new records to the bank_accounts table, which has columns for account_holder and balance. It inserts three rows: Alice with 1000.50, Bob with 2500.75, and Charlie with 1500.25. This creates new entries for each person along with their balance. The balance column uses the NUMERIC(15, 2) data type. The number 15 means that the total number of digits can be up to 15. The number 2 means that there can be up to 2 digits after the decimal point.

Option C: FLOAT in SQL 

The FLOAT type is used to store floating-point numbers, which are numbers that can have a fractional part (decimal). FLOAT doesn’t give exact accuracy like NUMERIC, which stores exact values. FLOAT is used when you need to store very large or very small numbers that may require rounding.

Example : 

CREATE TABLE product_prices (
    product_name VARCHAR(50),
    price FLOAT
);

In this example, we create a table named “product_prices”, where the price column uses the FLOAT data type to store the prices of products. This allows for decimal values but with approximate accuracy.

Option D: ALL THE ABOVE 

As we discussed all the above-mentioned options are valid SQL types, and each of them has their own usage, like:

  • CHAR is used to access fixed-length strings,
  • NUMERIC is used for exact numeric values with specified accuracy and scale
  • FLOAT is used for approximate numeric values with floating decimal points.

Hence, we can say all the above options are correct.

Conclusion

The above-mentioned options FLOAT, NUMERIC, DECIMAL, and CHARACTER all are valid SQL types that are used to handle different kinds of data with accuracy and efficiency. Each data type is designed for specific use cases, ensuring accurate storage and calculations.

About the Author

Data Engineer

As a skilled Data Engineer, Sahil excels in SQL, NoSQL databases, Business Intelligence, and database management. He has contributed immensely to projects at companies like Bajaj and Tata. With a strong expertise in data engineering, he has architected numerous solutions for data pipelines, analytics, and software integration, driving insights and innovation.

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