I wonder which part is performance unmatched?
My opinion would be Crystal language for its simplicity and higher throughput but unmatched performance is behind Rust and C.
That, or it can be read as "in the family of web-friendly languages". The only other "fast" language widely used for the web is Java.
With (in my experience) go being a little faster than java and haskell, and o'caml being slightly faster than anyone, but nothing significative enough for me to expect an article titled "my Java webapp was too slow so I rewrote it in O'Caml" anytime soon.
Benchmarking is very relative, though. I'd be glad to read evidence showing go is significantly slower than any of those in some domain.
You know you can contribute what you consider to be better examples — https://salsa.debian.org/benchmarksgame-team/benchmarksgame/...
> …or even best algorithms…
Wouldn't that make the algorithm the difference ;-)
You seem to be saying that what you see on the benchmarks game matches your experience, which makes your "highly biased" claim kind-of strange.
Please show something on that website that is "highly biased".
Yes it is hard to tune, but not so much different than playing with C or C++ compilation switches, across each compiler that is being used in production.
Go uses an order of magnitude less memory for most type of workloads though. Also you don't tune c++ binaries delivered to you. You have to tune the JVM's option to death for big apps. I can't count the number of incidents "solved" by raising the Xmx param.
The big question is how properly those big apps were coded.
Go doesn't run Fintech servers, while Java keeps replacing C++ servers. Yes, one needs to code Java with low level tricks like C++, but it is possible and there are many performance experts doing it.
How many Fintech servers are running on Go?
How many customers run self-compiled, say mysql binaries? Or mongodb? An tiny minority. Now how many tune cassandra or hadoop jvms? A big chunk.
You can use niche cases to make a point (fintech is almost the textbook definition of a niche software use case), however what you say is plain wrong most of the time.
Also, I've managed thousands of c++ and thousands of java processes. I'd take c++ ones over java any day.
Proper Cassandra and Hadoop deployments are as niche as Fintech, the large majority could solve their problems with UNIX command line tools.
On my world the team manages deployments, I rather take Java over C++ compilation times, and having tools like Mission Control to monitor cluster performance on production servers.