SQL vs Python

SQL vs Python

Think about a Swiss Army Knife and a wrench. The Swiss Army Knife has multiple tools to handle different tasks. And a wrench is a specialized tool designed for a specific purpose;  tightening or loosening bolts.

Similarly, Python is a multi-purpose programming language used for a wide range of applications like data analysis, web development, machine learning, and more.

And SQL is excellent for manipulating and organizing data in a database.

Both Python and SQL have their unique strengths and purposes, and just like Swiss army knife and wrench, Python, and SQL together can work in tandem to accomplish complex tasks.

This blog will compare SQL and Python and suggest which one you should choose.

Introduction to SQL and Python

SQL (Structured Query Language) is a database language used for managing databases.

SQL organizes data into tables and links data between them. We also use SQL to gain data insights, perform data analyses, and retrieve records from extensive databases.

Now, what's Python?

Python is a programming language used for various tasks, such as back-end development, data science, machine learning, and writing system scripts.

Python is a language with readable syntax. It's the most accessible language available today.

Differences Between SQL and Python

Here's how the code of SQL and Python differs:

Suppose  we have a table called "employees" in a database, with columns "id," "first_name," "last_name," and "salary." We want to find all employees whose salary is above $100,000.

SQL Command

SELECT first_name, last_name FROM employees WHERE salary > 100000;

Python Code (using pandas library)

import pandas as pd
employees = pd.read_sql_query('SELECT * FROM employees', connection)
selectedEmployees = employees[employees['salary'] > 100000]
print(selectedEmployees[['first_name', 'last_name']])

Notice that we integrated SQL with the help of a Python library, pandas. This shows that we need SQL to perform database-related tasks in programming.

Career Paths

A career in SQL leads to jobs like database administrator, data analyst, and data scientist.

These professionals are responsible for designing and maintaining databases, writing SQL queries to retrieve and manipulate data, and analyzing data to identify patterns and insights.

A career in Python leads to jobs like data analyst, machine learning engineer, and software developer.

These professionals are responsible for analyzing data, developing algorithms, building predictive models, and developing software applications.


According to Glassdoor, the average salary of SQL careers are

SQL Careers

Average Salary

Database Administrator 


SQL Data Analyst


Data Scientist


The average salary of Python careers are

Python Careers

Average Salary

Machine Learning Engineer


Data Analyst


Software Engineer


Which One Should You Learn: SQL or Python?

Learn both SQL and Python to maximize your job prospects and improve your skills.

SQL is often used in conjunction with a programming language like Python. And Python requires a database language such as SQL to interact with databases.

Therefore, learning both languages is highly recommended if you're pursuing a career in software engineering, machine learning, or data analysis.

The best way to learn any technical skill for beginners is through interactive courses. These courses test your knowledge after each new topic and give you quizzes and challenges to solve.

We suggest you go through Learn SQL Basics for the best interactive SQL course for beginners.

For Python, check out Become a Python Master.