Every programming language has its 'killer' domain
55 comments
·May 18, 2025valorzard
C# is also THE language for game developers. No other language even comes close, besides like C++
seabrookmx
It also runs on non "Microsoft systems."
I've been writing C# for over a decade, and 99% of it has deployed in Docker containers to Linux VM's (via k8s etc).
This post seems nonsensical.
notpushkin
It doesn’t say you can’t, or shouldn’t, use these languages for other purposes.
Edit: nvm, see jibal’s comment below
jibal
"in my experience each time I try to use a language in the wrong domain, it's much harder and often practically infeasible."
oliverdzedou
C# is definitely popular for game development, but saying no other language comes close does not seem to be true. Looking at the most popular game engines and frameworks, it seems to be about as represented as anything else.
Game engines: Unreal - C++, Unity - C#, Godot - GDScript (Python) + second-class C# support
Frameworks: Raylib - C, Bevy - Rust, Love2D - Lua, Monogame - C#, Phaser - JS, PyGame - Python
We don't know for sure what AAA companies rolling their own engines use, but the industry standard would be written in C++, exposing C++ for programmers and Lua for non-programmers/modders.
worthless-trash
More games are written in javascript than any other language, sad but true.
dedup
To me, Python is a great language for anything that needs to be written quickly and executed a few times and/or on a small scale. I'm a C/low-level guy primarily but I write a lot of Python code (probably more than C these days) for various purposes, and none of it is related to statistics or machine learning.
morepedantic
Because you haven't extrapolated from Python's niche. Those domains are derived from Python's accessibility. Python might be the most accessible big boy language.
andirk
I'm currently learning Python for my ML/Tensorflow online coirses. I thought bc I know C++ it'd be super easy but theres a lot of differences between them. Turns out an "easier" big boy language still has a bit of a learning curve
condwanaland
I strongly think that R has outgrown just having statistics as its killer feature. The killer feature of R is data analysis
I have yet to see any software that rivals dplyr, data.table, and ggplot2 in the balance of power and ease of use. It also has all the auxiliary packages you need to fetch your data (DBI, httr, rvest), model it if necessary (parsnip, caret) and visualise it (ggplot2, plotly, shiny)
I know python is more popular here but I would choose R in a heartbeat 19 times out of 20
andirk
Is Python especially popular because of its easier learning curve?
condwanaland
Possibly. I think R is actually easier to learn for people who have never studied or done programming before.
1. It's easier to get up and running as RStudio is much more 'batteries included' than other popular IDEs, it's harder to get into the case of multiple different python versions, and you install packages through the R interpreter rather than via pip at the command line
2. I would say R data analysis packages are easier to learn than the python equivalents. Because the dataframe is a native structure in R there has been a lot more packages that have tried alternative syntax approaches to try and find the 'optimal' one. Python has really only had pandas, polars, and pyspark (all of which have implemented their own data structures and therefore have focused more on performance than syntax)
3. This doesn't hold if you're studying a language to be a general purpose programmer. Then python is much better. Anything to avoid the hell of the R standard lib. But if you need to do a bit of coding to analyse data and you've never done any before, my vote would be for R.
However, these are thoughts from my own personal anecdotes rather than any pedagogical theory
-__---____-ZXyw
I wonder what Common Lisp's 'killer domain' is in this framework... general purpose computations? Which was a bit much to handle for businesses and even a lot of programmers, hence its niche (yet actually very resilient) status?
sedatk
“C# → Business applications that run on Microsoft systems.”
Folks, it’s 2025. This stereotype should have died at least five years ago. C#+.NET is open source and cross-platform since 2016 or so.
vaylian
Did C# really catch on on other platforms? C# was somewhat popular on Linux with Gnome for a while but my impression is that this has completely died down.
While it is technically possible to use C# on Linux and MacOS, it doesn't seem to have a significant mind share.
oaiey
Surely there is somewhere a number, but my educated guess is that 90% of all new / greenfield deployments go into a Linux (or a Lambda/Docker variant).
dgrin91
Not to mention c# is commonly used for video games (see: unity)
mg
Python → Scientific computing and machine learning.
PHP → Web backend.
Not sure how to figure it out. Google trends maybe?
https://trends.google.com/trends/explore?date=all&q=python%2...
maz1b
Elixir/Phoenix? Haskell? Erlang? F#? Crystal?
I also don't agree with the fact that ruby is just like PHP.. for web backends.
notpushkin
Elixir/Phoenix → web, various parallel processing stuff?
Haskell → dunno, but it’s pretty cool
Erlang → dunno again, maybe some low-level stuff for Elixir?
F# → business apps for MS when you get sick from C#
Crystal → web, I guess?
Ruby is good for web, but it’s also useful when metaprogramming tricks work for you in your particular domain. Same with Python (it’s also insanely good for web!).
simonmic
Haskell → High-assurance applications and prototyping/research.
rienbdj
F# is strictly better than C# if (huge if) you have a team that knows both languages.
notpushkin
It’s an important caveat, yeah!
asplake
Erlang → scalable real-time systems, eg telecoms
notpushkin
Yes, though could you perhaps use Elixir there as well? (Sorry, I’m still largely ignorant to this space, but would love to learn more!)
harrall
IMO ecosystem, tooling and support is what makes a language mainstream. Having a domain is something that comes afterwards.
e.g.
* Ruby had Rails
* PHP had mod_php and a strong Apache-oriented community
* Java had strong support from Sun
* Python for scientific computing because of numpy, etc.
If numpy and friends were made for Ruby instead, I think we’d be in a different world.
setopt
I think it’s more that languages fail to go mainstream unless they have a killer domain. Lots of languages don’t.
geomcentral
Java isn't really used to develop Android apps any more, especially now that Jetpack Compose is here:
Java → Business applications
Kotlin → Android
rienbdj
What this skips over is that some languages are better than all others in a domain, sometimes multiple domains. And also some languages are not best in class in any domain.
Would you pick Brainfuck over Java for anything (real)?
null
defrost
If alternative programming exercise counts as a domain, then yes ..
along with Turing Tape machine coding, corewars, that one from Knuth ..
outside of that domain of interest, not so much.
But that is one domain of interest.
It's also true that real world industrial scale dam control isn't a killer application domain for Brainf*ck .. but FGS, have you seen many SCADA implementations?
I think the thing missing here is that the killer domain isn't necessarily intrinsic to the language or its design. Some languages are designed for specific domains, but some find their domain based on large projects that happened after the language was out in the world. My understanding is rails came almost a decade after Ruby, numpy etc came well after python. This post says that you shouldn't try to use a language outside of its domain, but if everyone believed that, languages would never find a new domain.