Ugh, I just... I keep trying to pretend I don't need to learn Go, but every highly scalable system I read about that's recently been written about seems to be using it. Maybe I just need to stay away from systems that need to scale? Heh...
Technically speaking you can build scalable systems using anything you want. But if you need to hire a couple of hundreds developers, you better go with Java 7 or Go than Ruby, Lisp or Perl. The dumber and more uniform the better.
I very much doubt that anyone is using Crystal at the scale Ruby/Rails is used yet. It's still far away from a 1.0 release and when I tried out 0.23 it had several issues, major ones for me were lacklustre debugging support and the type checker needing to load the whole AST into memory. Concurrency story was also not very strong but I know people were working on it actively at least.
Anyway, I wrote a non-trivial project in Crystal and overall really enjoyed it. Improving the debugging tooling would go a long way towards making it a real option.
Still, you definitely do not need Go to scale systems. People scale Everything, perhaps most impressively PHP applications.
You're just seeing golang in articles because of hype.
Two areas where it is actually slower are
1) Memory allocation 2) Regular expression performance.
But you must understand your Java app won’t have performance advantage because of faster alloc speed IRL: GC will take lots of CPU, because Go’s one is much easier at memory release. You can only see allocation advantage in micro benchmarks where the app stops before the GC will start.
Request / response servers which keep caches and other allocations prone to middle age death out of the GC heap are consistent with the generational hypothesis and ought to spend no more than a few (low single digit) percent in GC with a generational collector.
The golang gc is tuned for latency at the expense of throughput, meaning if you look at the duration of time spent in GC over the course of the code execution, it would actually be longer compared to a GC tuned for throughput.
If you have a use case that requires high throughput, then you cannot change the GC behavior. Unlike on the JVM, where you have several GCs to choose from. The JVM is also getting two new low latency GCs for use cases that require low latency.
And it's not just microbenchmarks where Java does better than golang, it's especially longer running processes where the JVM's runtime optimizations really kick in. Not to mention that the JVM is getting value types as well to ease the load on the GC when required (it does an excellent job as it is even without value types).
I did a dummy port of the C# version of the Havlak code here[1] to Java, preserving the same behavior and not making any data structure changes. On the machine I tested on, the C# version took over 70 seconds to run, while the Java version took ~17 seconds. In comparison, the C++ version took ~24 seconds, and the golang version took ~30 seconds.
Yes, you could most likely spend much more time tuning the C++ version, avoiding allocations, and so on, but at the expense of readability. This is what the JVM gives you, you write straight-forward, readable code, and it does a lot of optimizations for you.
The brainfuck2 benchmark is especially interesting. Kotlin tops the list, but I was able to get Java to the same performance since Kotlin by writing it in a similar manner as the Kotlin code. Again, Java/Kotlin beat out even C++ when I tested them, and by quite a margin.
https://www.techempower.com/benchmarks/#section=data-r17&hw=...
c#, rust, go, c++, java, c, nim.. all tied at 7M.
again, this doesn't mean anything useful.
What you're probably referring to is GC pauses. The golang GC is tuned for latency, at the expense of throughput. The JVM has several GCs, and is gaining several more like Shenandoah and ZGC, which allows you to select the GC that best fits your use case. You can tune for latency or throughput.
A lot of Java deployments these days are in the form of uber/shaded jars, which is basically one jar file that contains the entire app, and run with a single command, not much different than running a binary.
Crystal is still immature, Rust is more suited to use cases where you want to avoid garbage collection.
Hype is not the only factor but it makes hiring easier. And anything Google puts its weight behind will get hyped. More often than not it's better to choose a technology which suits your organisational (read: hiring) needs.