When Escape Routes Become Toll Roads: Mapping How Developers Move Between Programming Languages

Vladimir Volokhonsky

TL;DR: This post relates findings about language migration from the 2025 State of Developer Ecosystem survey. In general, project requirements are still the most common reasons for switching languages. One outlier from this trend, however, is Kotlin. People switch to Kotlin not because they have to; they switch because it simply feels better to work with, thanks to its better development experience and more modern features. C has a surprisingly high churn rate, and Java developers tend to move to Python and TypeScript. HTML/CSS developers learn JavaScript to improve their job opportunities, while JavaScript developers switch to almost everything else for the same reason.

The history of programming is, in part, a history of escape

Ada Lovelace wrote for a machine that did not yet exist in working form. A century later, programmers were wrestling with machines that had switches, punched cards, and raw numeric instructions. Then came assembly, and with it the first great bargain of software: give up a little closeness to the machine, and gain a little room for the human mind. But history does not stand still. With new languages and shifts in context, aspects of existing languages began to get in the way.

One language moved to such a high level of abstraction that its efficiency in the physical reality of the machine stopped holding up. Meanwhile, the fast-growing Internet of Things meant that programs now had to run on a coffee machine in a sense that was no longer metaphorical. In some places, development speed was missing. In others, safety was.

We escaped from assembly into C, from C into managed runtimes, from ceremonial enterprise Java into Kotlin, from dynamic-language freedom into TypeScript, from unsafe systems code into Rust, and from heavy frameworks into smaller cloud-native tools. At first glance, all migration channels seem clear. But how does this map onto reality?
Quite a lot of material, in one way or another, measures how the popularity of programming languages changes over time. Yet it seems that no one has really looked at the broader picture of how programmers themselves move between languages – not from the point of view of global trends in software development, but from the point of view of an individual path.

For us at JetBrains, it is very important to get closer to understanding what is happening from the programmer’s perspective, rather than from that of a programming historian or a career adviser. This is the perspective that matters most to us. In this spirit, we designed our State of Developer Ecosystem surveys with the goal of illuminating what the path of a real programmer looks like. Here’s what we found in 2025.
First, we should acknowledge that the path between languages can look like almost anything. Yes, the most common routes are between the leading languages: from Python to Java and back, with Java to Kotlin in third place by absolute numbers. But people migrate in every possible direction.

But we’ve gotten ahead of ourselves. Let’s take things one step at a time.

What we did before and what we achieved in 2025

Since the beginning of the Development Ecosystem survey, we have used the question “Do you plan to adopt or migrate to other languages in the next 12 months? If so, which ones?” We quickly found, however, that it is not a good predictor for future language migration. It’s one thing to plan to try Rust or switch from Java to Kotlin, but even for very common moves, the number of developers who actually make the switch is much lower than the number of those who have plans. Just because we have issues supporting our old Java 8 codebase, for example, doesn’t mean we’ll actually leave it.
So last year, we added a new set of questions regarding respondents’ previous experience with programming languages. We decided to assess actual migration over the past year using the question “What were your primary programming languages 12 months ago?” and some other related ones. This report addresses these questions, as well as the programming language landscape as a whole, based on the 8,837 responses we collected.
For reference, the following terms refer to the answers of the corresponding questions:
Used language – “Which programming languages have you used in the last 12 months?”
Primary language – “What are your primary programming languages? (Up to 3)”
Main language – “What is your main programming language?”

This сhart is based on the responses to the question “Which programming languages have you used in the last 12 months?” The increase in Java and Kotlin shares is most likely the result of a shift in the sample, rather than a real trend. The main fast risers are TypeScript and Rust, as we described in our 2024 Developer Ecosystem infographic. We also predicted some growth for Python, Go, and Lua, but only Go showed actual growth.

JetBrains Language Promise Index

The Language Promise Index tracks the migration prospects of languages in arbitrary units, based on the data we had on the stability of positive or negative migration dynamics and the number of people wishing to learn the language. Lua was previously one of the top languages in this category, but its growth has apparently reached a certain ceiling, and it is no longer among the leaders.

TypeScript, Rust, Python, and Go all still have large growth potential. We expect that a lot of people would change their main language from JavaScript to TypeScript while still using JS as their secondary language. 

As you can see, despite being the most popular language in terms of overall usage, JavaScript is the main language for only 6% of software developers, while Java is still much more popular as a main language. 

Unfortunately, we don’t have enough answers for most programming languages, so the next tables include only the most popular ones.

Surprisingly, C shows the lowest retention. About half of those who said that C was their main language last year have now switched to something else. This is a bit strange. Initially, we assumed that this flow probably consisted of students who had adopted C through their education and then switched to another language. However, the experience level has only a small effect. Half of those who dropped C chose “I wanted to learn a new language” as the reason for their change, which has a higher share than among switchers from other languages, who mostly chose “A project I am working on requires the usage of a new language.”
However, we didn’t have such questions for last year and do not see so much churn for C based on a comparison of shares with previous-year data (2.1% this year as a main language vs 2.0% in last year). But this churn rate may be a good predictor of future changes.

Why developers leave – and where they go

First of all, we should say that we don’t have data about everyone who churned – people who retired or switched to another career path don’t typically answer our developer surveys. Nevertheless, we do have enough information to draw some conclusions about why people decide to switch from one language to another.

Note: The sample is extremely small (less than 100) for C, Kotlin, and PHP.,
Some findings from this data:
1. Project requirements are the most common reasons for switching languages.
2. As we mentioned before, for C, “I wanted to learn a new language” and “More modern language features” are very popular reasons for switching, which probably point to widespread dissatisfaction and the language’s aging.
3. For JavaScript, the reason people leave is often “Better job market opportunities”.
4. Performance and scalability limitations are often a reason to switch from PHP.
5. “Other” reasons accounted for 18% of Kotlin churners. According to their answers, they are switching companies and switching between hobby and professional use.

The following tables, where both rows and columns list the same programming languages, require some additional explanation. Each one depicts the shift in respondents’ main languages. In the first, the columns are divided by last year’s responses for a given language, and the rows show the languages that respondents have moved to. Conversely, the second tracks where new language users are coming from, with the columns divided by respondents’ current main languages and the rows showing their previous answers. Each column totals 100%, because it tracks the same population over the course of a year. 

The tables show transitions from seeing one language as your “main” language to seeing another language that way. This does not mean that people stopped programming in the “abandoned” language altogether. It simply means that it stopped being their primary language.

This table shows where people go based on their previous language. Python is the main switch destination for all languages except C (whose users preferred to move to Java and C++) and TypeScript (where the top target destinations were Java, JavaScript, and C#).

Why developers adopt – and where they come from

Let’s look at the inverted perspective, based on the language to which people migrated.

Some findings from this data:

1. Surprisingly, JavaScript is both the main language people leave for better job market opportunities and the one people move to for the same reason. But these flows are not the same: one of the main sources for JavaScript growth is HTML/CSS. So, the pattern looks a bit like a conveyor belt: HTML to JavaScript to TypeScript. 
2. Project requirements are very common reasons for switching to C# and C++, suggesting many developers switch to these languages simply because they have to. 
3. People don’t go to Kotlin because they have to, but because it offers a better development experience and more modern language features.
4. Performance and scalability are the main attractions of Go, whereas ecosystem and library support are stronger attractions for Python.

At first glance, the following table may look the same as the main-language churn table above. But it is actually completely different, with a different meaning.

Here, the language that respondents see as their main language at the time of answering is taken as 100%. Accordingly, the diagonal shows what we called the continuity rate: the share of people who use this language as their main language now and also used it as their main language a year ago. Imagine that we have 150 respondents. Of them, 100 said they use a certain language as their main language this year, while 125 said they used it as their main language last year. 75 people used this language as their main language both a year ago and at the time of the survey.

In this case, the retention rate would be 75%, while the continuity rate would be 60%. It is important to note that everyone else is not necessarily a “newcomer” to the language. They may well have used this language before, just not as their main one.

In terms of growth sources, Python is the main source for C, C#, C++, Go, Java, and JavaScript, which is not surprising, because it is one of the most popular languages.

For Kotlin, the main growth source is Java, while for PHP and TypeScript, it is JavaScript.

For Python itself, the main growth source is Java. 

Conclusion

By looking at actual moves instead of plans, we shift from intention to action – not what developers say, but what they do. The ecosystem data stops being a snapshot and starts to look like a map of flows.

Project requirements still do most of the pushing. Necessity, not choice, drives many switches, but not all. Some languages win on specific jobs, others on performance or ecosystem. And many developers move in chains: from HTML/CSS to JavaScript, and then further along – a conveyor belt of skills, where each step opens the next.

Churn tells a clearer story. C leaks talent faster than expected, even if its headline numbers look stable. Java remains a hub, but its outflow goes mostly to Python and TypeScript, not Kotlin. Python acts as a catch-all destination. TypeScript and Rust still look like the forward edge.

Kotlin, our own language, plays a different game – and plays it well. Developers come not because they have to, but because they want to, drawn by cleaner syntax, fewer rough edges, and a development experience that simply feels better. It wins on pull, not push. Yet the inflow from Java is weaker than expected, and some developers even switch back.

The picture that emerges is a simple one of push, pull, and drift. With the new data, we see not just which languages grow or shrink, but how it happens – which languages move with the current, and which have to work against it.

Let’s see what DevEco’26 will reveal.