Earlier this year, Stack Overflow’s annual developer survey was released with over 90,000 responses about which technologies developers are using, what they’re most excited about, etc.
I decided to dive a bit deeper into the top 10 programming languages that are currently used by developers today.

Most Popular: JavaScript, HTML/CSS and TypeScript
The most popular languages are currently JavaScript and HTML/CSS, with TypeScript coming in at #5. These languages are mainly used for web development and were all introduced within the past 30 years. TypeScript, which enhances JavaScript development, is the newest player of the three and was created just over 10 years ago by Microsoft.
Most Versatile: Python
The third most popular programming language at the moment is Python. Python is widely used by both beginners and experienced programmers. While its syntax is relatively straightforward, it can be quite powerful and handle large data sets and complex tasks.
Another notable characteristic of Python is that it’s used within a variety of domains, from data analysis to game development to web development.
Personally, as a data scientist, it’s my favorite programming language (check out my recent Data Science in Python course) and I think it’s a great first programming language to learn.
The Backbone: SQL
One reason it’s so surprising to see SQL in the top four is that it’s on the older end – it was introduced to the world almost 50 years ago! That said, it’s still going strong.
SQL is the language used for working with relational databases, which is where companies typically store their data. That means that anyone who wants to access company data will likely need to write SQL code to do so, including:
Web developers who mainly code in HTML / CSS / JavaScript
Software engineers who mainly code in Java
Data scientists who mainly code in Python
Along with their main programming languages, people in all these roles will also use SQL to work with structured data, which is why you see SQL as a part of so many tech stacks.
The Assistant: Shell
The shell is a general term used to describe programs that provide a command line interface, including Bash, Zsh, PowerShell, etc. These scripting languages allow you to interact with a computer’s operating system and perform tasks like automation, batch processing, interacting with version control systems like git, etc.
The Workhorses: Java, C#, C++ and C
These general purpose programming languages round out the top 10. They’re known for their versatility, performance, and wide range of applications. Most computer science majors will learn at least one of these in school. The programming languages were created from the 1970s to the 2000s, and continue to have relevance today in the ever-evolving landscape of software development.

Up to 50% Off Maven Pro Plans!
FLASH SALE
Take advantage of this limited-time offer and save up to 50% off unlimited Maven access!

Alice Zhao
Lead Data Science Instructor
Alice Zhao is a seasoned data scientist and author of the book, SQL Pocket Guide, 4th Edition (O'Reilly). She has taught numerous courses in Python, SQL, and R as a data science instructor at Maven Analytics and Metis, and as a co-founder of Best Fit Analytics.
Frequently Asked Questions
What is Maven Analytics?
Maven Analytics is an online learning platform that helps professionals and organizations build practical data and AI skills in analytics, business intelligence, and data science. Our hands-on courses are designed to help learners stay competitive and future-proof their careers in the age of AI.
Are data analysis and data science still good career paths?
Absolutely. As long as companies collect and use data, they need people who know how to turn that data into results. Roles are changing, and so are the skills needed to succeed, but the career paths remain strong. Focus on data literacy fundamentals, business thinking, communication skills, and learning how to use modern data and AI tools, and you can build a strong career.
Will AI replace data jobs?
AI is changing how data professionals work, but it is not replacing the need for skilled analysts and data scientists. Instead, AI is becoming another tool in the data workflow. Organizations still need people who can ask the right questions, interpret results, communicate insights, and apply data to real business decisions. The most successful professionals will be those who learn how to combine core data skills with modern AI tools.
How can I future-proof my career in analytics?
Future-proofing your analytics career means building strong core data skills, understanding business context, and learning how to work effectively with AI rather than compete with it. The goal is to become a better analyst, problem solver, and decision-maker.
How long does it take to build job-ready data skills?
That depends on your starting point and goals, but many learners can build meaningful skills over a few months with consistent practice, even when studying part-time. The most important factor is applying what you learn through hands-on projects and real business problems.






































