MySQL vs PostgreSQL vs SQL Server overview - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select all columns from a table named 'employees'.

SQL

SELECT [1] FROM employees;

Drag options to blanks, or click blank then click option'

AALL

B*

CEVERY

DCOLUMNS

Attempts:

3 left

💡 Hint

Common Mistakes

Using keywords like ALL or COLUMNS which are not valid in this context.

Trying to write column names instead of using the wildcard.

In SQL, * means select all columns from the table.

2fill in blank

medium

Complete the code to filter rows where the 'age' column is greater than 30.

SQL

SELECT * FROM users WHERE age [1] 30;

Drag options to blanks, or click blank then click option'

A<

B<=

C=

D>

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' which filters the wrong rows.

Using '=' which only matches exactly 30.

The symbol > means 'greater than' in SQL conditions.

3fill in blank

hard

Fix the error in the SQL query to count the number of rows in the 'orders' table.

SQL

SELECT COUNT([1]) FROM orders;

Drag options to blanks, or click blank then click option'

A*

Border_id

Call

Drows

Attempts:

3 left

💡 Hint

Common Mistakes

Using COUNT(all) or COUNT(rows) which are invalid.

Using COUNT(column) which may miss rows with NULL in that column.

Using COUNT(*) counts all rows regardless of NULLs.

4fill in blank

hard

Fill both blanks to create a query that selects the 'name' and 'salary' columns from 'employees' where salary is at least 50000.

SQL

SELECT [1], [2] FROM employees WHERE salary [3] 50000;

Drag options to blanks, or click blank then click option'

Aname

Bsalary

C>=

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>=' which filters wrong rows.

Selecting wrong column names.

Select name and salary columns, and filter salaries greater than or equal to 50000 using >=.

5fill in blank

hard

Fill all three blanks to create a query that counts how many employees have a department ID less than 10.

SQL

SELECT COUNT([1]) FROM employees WHERE department_id [2] [3];

Drag options to blanks, or click blank then click option'

A*

B<

C10

Ddepartment_id

Attempts:

3 left

💡 Hint

Common Mistakes

Using COUNT(department_id) which misses NULLs.

Using wrong comparison operators or values.

Use COUNT(*) to count all rows, filter where department_id < 10.

Practice

1. Which database system is known for easy setup and is commonly used in web projects?

easy

A. Oracle

B. PostgreSQL

C. SQL Server

D. MySQL

Solution

1. Step 1: Understand the common uses of MySQL

   MySQL is widely recognized for its easy installation and is popular in web development.

2. Step 2: Compare with other databases

   PostgreSQL is more feature-rich for complex queries, and SQL Server is suited for Windows business environments.

3. Final Answer:

   MySQL -> Option D

4. Quick Check:

   Easy setup and web use = MySQL [OK]

Hint: Think 'easy web projects' and pick MySQL [OK]

Common Mistakes:

• Confusing PostgreSQL with MySQL
• Choosing SQL Server for web projects
• Choosing Oracle, which is enterprise-focused

2. Which of the following is the correct way to start a SQL Server service on Windows using command line?

easy

A. service start sqlserver

B. net start MSSQLSERVER

C. systemctl start sqlserver

D. start-service sqlserver

Solution

1. Step 1: Identify Windows command for services

   On Windows, the command to start services is 'net start' followed by the service name.

2. Step 2: Recognize SQL Server service name

   The default SQL Server service is named MSSQLSERVER, so the command is 'net start MSSQLSERVER'.

3. Final Answer:

   net start MSSQLSERVER -> Option B

4. Quick Check:

   Windows service start = net start MSSQLSERVER [OK]

Hint: Windows services start with 'net start' [OK]

Common Mistakes:

• Using Linux commands like systemctl
• Using incorrect service names
• Confusing PowerShell commands

3. Given the following SQL query run on PostgreSQL:

SELECT LENGTH('Hello World');

What will be the output?

medium

A. 10

B. 12

C. 11

D. Error

Solution

1. Step 1: Understand LENGTH function in PostgreSQL

   The LENGTH function returns the number of characters in the string.

2. Step 2: Count characters in 'Hello World'

   There are 11 characters including the space between Hello and World.

3. Final Answer:

   11 -> Option C

4. Quick Check:

   Count characters including space = 11 [OK]

Hint: Count all characters including spaces [OK]

Common Mistakes:

• Ignoring the space character
• Confusing LENGTH with LEN
• Expecting error due to function name

4. You try to run this query on MySQL:

SELECT TOP 5 * FROM users;

But it gives an error. What is the problem?

medium

A. MySQL does not support SELECT TOP syntax

B. Missing WHERE clause

C. Table 'users' does not exist

D. Incorrect use of semicolon

Solution

1. Step 1: Recognize SELECT TOP syntax usage

   SELECT TOP is used in SQL Server to limit rows, but MySQL uses LIMIT.

2. Step 2: Identify correct MySQL syntax

   In MySQL, the query should be: SELECT * FROM users LIMIT 5;

3. Final Answer:

   MySQL does not support SELECT TOP syntax -> Option A

4. Quick Check:

   MySQL uses LIMIT, not TOP [OK]

Hint: MySQL uses LIMIT, not TOP [OK]

Common Mistakes:

• Assuming TOP works in MySQL
• Thinking WHERE is mandatory
• Blaming semicolon usage

5. You want to use a database system that supports advanced JSON querying and complex data types for a data analytics project. Which database is the best choice?

hard

A. PostgreSQL

B. MySQL

C. SQL Server

D. SQLite

Solution

1. Step 1: Identify database strengths for complex data

   PostgreSQL is known for powerful features including advanced JSON support and complex data types.

2. Step 2: Compare with other options

   MySQL has JSON support but less advanced; SQL Server supports JSON but is more Windows-focused; SQLite is lightweight and limited.

3. Final Answer:

   PostgreSQL -> Option A

4. Quick Check:

   Advanced JSON and complex data = PostgreSQL [OK]

Hint: Pick PostgreSQL for complex data and JSON [OK]

Common Mistakes:

• Choosing MySQL for advanced JSON
• Selecting SQL Server for cross-platform JSON
• Picking SQLite for heavy analytics