SQL has slipped in popularity! Discover the reasons behind the changing trends in database languages and what’s taking its place. #SQL #NoSQL #ProgrammingTrends
Explanation in video
Hey there, tech explorers! John here, back with another dive into the fascinating world of AI and the tech that makes it tick. You know, keeping up with all the latest buzz can feel like trying to drink from a firehose, especially when it comes to the nitty-gritty details of programming languages. But don’t worry, that’s why Lila and I are here – to break it all down for you!
What’s the Buzz About SQL?
Recently, a big “popularity contest” in the tech world showed some interesting shifts, and one language, in particular, got a lot of attention for slipping a bit. We’re talking about SQL.
Now, SQL has been around since the 1980s, and for a long time, it’s been the go-to tool for managing information in a very specific type of digital storage.
Lila: Hold on, John! You just said SQL and then “managing information in a specific type of digital storage.” What exactly is SQL, and what kind of storage are we talking about?
John: Great question, Lila! Imagine you have a massive library, and inside it, every book has a specific place on a specific shelf, organized by title, author, genre, and so on. If you want to find all books by “Smith” in the “Science Fiction” section published after 2000, you’d need a very precise way to ask for that information, right?
Well, SQL (which stands for Structured Query Language) is like the special language you use to talk to that library’s super-organized catalog system. It helps you ask for, update, or even remove information from these highly structured digital libraries, which we call relational databases. Think of a relational database as a collection of super-organized tables, much like spreadsheets, where everything is neatly categorized and linked together. SQL is the tool you use to manage all that neatly arranged data!
The Popularity Contest: Tiobe Index
So, why is SQL in the news? Because in the latest “report card” for programming languages, it’s dropped a few spots. This report card is called the Tiobe Index.
Lila: A report card for languages? What’s the Tiobe Index, and how does it even work?
John: Good point, Lila! The Tiobe Index is like a monthly popularity ranking for programming languages. It doesn’t just guess; it actually measures how often a language is mentioned or searched for across the internet, checking things like the number of skilled engineers using it, courses available, and companies offering services related to that language. They look at major websites like Google, Bing, Amazon, Wikipedia, and many others to get a broad picture.
In their latest June 2025 ranking, SQL has fallen to 12th place, which is the lowest it’s ever been. This is a big deal because for decades, it was always a top player!
Fun fact: SQL actually had a bit of a bumpy ride on this index. Back in 2004, it was removed because some folks argued it wasn’t a “real” programming language. But then, in 2018, someone pointed out that it’s actually Turing-complete, which does make it a programming language, so it was added back!
Lila: Wait, Turing-complete? That sounds super techy. What does that even mean?
John: That’s a great observation, Lila! Don’t let the fancy name scare you. Being “Turing-complete” basically means a language is powerful enough to do any kind of calculation or problem-solving that a computer can theoretically do. Think of it this way: if a language is Turing-complete, it means you can use it to build any program that can solve any solvable computational problem. It’s like having a universal Swiss Army knife for computing tasks! So, SQL might not be used to build a flashy video game, but it has the fundamental power to handle complex logic, which makes it a legitimate programming language.
Why the Change? Blame it on AI (Kind Of!)
So, why the slip? Paul Jansen, the CEO of Tiobe, says SQL will “remain the backbone” of databases for a long time. However, he also points out that the booming field of AI is changing things.
He mentioned that for AI, where data is often “unstructured,” another type of database called NoSQL is often a better fit. He compared this shift to how languages like Python became popular over more traditional ones like C++ and Java.
Lila: “Unstructured data” and “NoSQL databases”? What are those? And what’s the difference between Python and C++ or Java in this context?
John: Excellent questions, Lila! Let’s break it down:
- Unstructured Data: Imagine your digital life. You have perfectly organized spreadsheets (that’s structured data), but you also have photos, videos, emails, social media posts, voice recordings, and random notes. These are all forms of unstructured data. They don’t fit neatly into those row-and-column tables of a relational database. AI loves this kind of data because it’s what makes up most of the real world!
- NoSQL Databases: Since relational databases are designed for super-neat, organized data, they struggle with unstructured stuff. That’s where NoSQL databases come in. “NoSQL” basically means “not only SQL.” These databases are much more flexible, like a giant, adaptable storage bin that can hold all sorts of different things without needing a strict pre-defined structure. They’re perfect for the messy, diverse data that AI models learn from.
As for Python versus C++ or Java, Paul Jansen was talking about how they handle information, specifically something called “typing.”
Lila: “Typing”? Is that like, how fast you can type on a keyboard?
John: (Chuckles) Not quite, Lila! In programming, “typing” refers to how a language handles different kinds of data, like numbers, words, or true/false values. There are two main types:
- Statically Typed Languages (like C++ and Java): Think of these like building with a specific Lego kit where each piece has a pre-defined shape and purpose. You have to tell the language exactly what kind of information you’re working with before you even start building. It’s very strict and helps catch errors early, but it can be less flexible.
- Dynamically Typed Languages (like Python): These are more like building with a giant bin of generic blocks. You can just grab a block and use it, and the language figures out what kind of “shape” or “purpose” it has as you go along. It’s much faster to get started and more flexible, which is great for quick experiments and handling diverse, often messy, AI data.
So, the rise of AI, with its need for flexible storage for unstructured data and the fast-paced, experimental nature of dynamically typed languages, is giving NoSQL and Python a big boost, which in turn means SQL isn’t quite as front-and-center as it once was.
Who’s Hot and Who’s Not? The Top 10 List!
Just for fun, here’s the Tiobe Index Top 10 for June 2025:
- Python, with a rating of 25.87%
- C++, 10.68%
- C, 9.47%
- Java, 8.84%
- C#, 4.69%
- JavaScript, 3.21%
- Go, 2.28%
- Visual Basic, 2.2%
- Delphi/Object Pascal, 2.15%
- Fortran, 1.86%
As you can see, Python is still holding strong at number one! But the Tiobe Index isn’t the only way to measure popularity.
Lila: Really? Is there another way? What is it?
John: There is! It’s called the Pypl Popularity of Programming Language index. Instead of looking at engineers or courses, the Pypl index measures popularity based on how often people search for language tutorials on Google. It’s a different way to gauge interest, focusing more on what people are actively trying to learn.
And here’s the Pypl Top 10 for June 2025:
- Python, with a 30.63% share
- Java, 15.36%
- JavaScript, 7.78%
- C/C++, 7.02%
- C#, 6.02%
- R, 4.63%
- PHP, 3.58%
- Rust, 2.97%
- TypeScript, 2.81%
- Objective-C, 2.79%
Again, Python is at the top, which really highlights its current importance in the tech world, especially with the rise of AI!
John’s Thoughts & Lila’s Takeaway
John: To me, this shift isn’t about SQL becoming irrelevant; it’s about the tech landscape evolving. SQL is still foundational for countless systems, but the sheer volume and complexity of AI data demand new tools. It just shows how dynamic and exciting the world of technology really is – always adapting to new challenges!
Lila: Wow, John! I always thought programming languages were just, like, behind-the-scenes magic. But hearing about SQL and NoSQL, and how AI is changing which ones are popular, makes it feel like these languages are alive and responding to what we need them to do. It’s fascinating how different types of “digital storage” are better for different kinds of information!
This article is based on the following original source, summarized from the author’s perspective:
SQL slips in language popularity index