While it's not surprising to me that the pure java implementation was far and ahead better since: 1.) Java's much faster than Javascript, and 2.) Netty (which Vert.x is based on), has been doing high performance async IO for years before node even existed in extremely high performance environments.
What is surprising however, is that javascript on the JVM w/ vert.x is faster than V8 with node. In both cases I would assume not much JS is executed, since in Vert.x most of the executing code is still Java, with a tiny piece of JS scripting on top, and in the Node.js case, I was under the impression that most of the executing code would be the C code that powers its HTTP server.
Does anyone with knowledge of the node internals know what's going on here? Is Node's HTTP parser just slower? Is its reactor not as efficient?
But there's no question Netty is fast even on a non-benchmark. I'm using it for a long-polling server with upwards of 100K connections, and my CPU doesn't go much over 5%. Besides memory usage, the main limitation has been proper kernel configuration.
https://github.com/carbonfive/hellod/blob/master/results.md
[1] C/libev, Clojure/Aleph, Clojure/Jetty, Erlang, Go, Java/Netty, Java/NIO, node.js, JRuby, MRI Ruby
V8 does heavy code optimization and Node.js http sever code should be well optimized as well. And maybe the load balancer for the multicore Node test isn't optimized enough. Thus, these results feel a little shady. Anyway, Vert.x was the trigger that I am finally downloading the JVM (JDK) to try Vert.x (and maybe later Clojure).
But there's still one major drawback—the non-existant ecosystem. I know the hint to look for libs from the Java world but I need a concrete and precise guide how to do this. Let's say I want to plugin some Java lib for image manipulation. How? And who will guarantee that these libs will be concurrent and/or non-blocking as well? The lib developer or Vert.x? At the moment there is—except few out-of-the-box modules—nothing. No 3rd party libs, no module manager a la npm and no guide or documentation how to glue Java libs to this Vert.x thing. Nothing. Correct me if I'm wrong.
Dude, I've been developing real-time military applications and we've moved from C/C++ to Java and got performance gains (I'm not saying that C can't beat Java doing specific computations - of course it can - but when building a large application with millions of lines of code and a large team of developers, Java would be a safer bet than C++ if speed is your concern). In other words, no other environment can beat the JVM.
And, yeah, you should try Clojure. It's a cathartic experience.
EDIT: The only doubts I have about vert.x is that it can consistently beat "old" JVM servlet containers under heavy, real-world loads. That remains to be seen.
importPackage(java.io); var file = new File('/blah/blah/blah.txt');
Other languages would be equally easy as well. It's burried, but here is some relevant information from the docs on integrating 3rd party libs:
-cp <path> The path on which to search for the main and any other resources used by the verticle. This is ignored if you are running an installed module. This defaults to . (current directory). If your verticle references other scripts, classes or other resources (e.g. jar files) then make sure these are on this path. The path can contain multiple path entries separated by : (colon). Each path entry can be an absolute or relative path to a directory containing scripts, or absolute or relative filenames for jar or zip files. An example path might be -cp classes:lib/otherscripts:jars/myjar.jar:jars/otherjar.jar Always use the path to reference any resources that your verticle requires. Please, do not put them on the system classpath as this can cause isolation issues between deployed verticles.
As far as concurrency, most libraries state in the docs what is threadsafe and what is not, so this is more or less "caveat emptor" and RTFM.
Vert.x has its own module subsystem which appears to package up .jar files and some glue code for the Vert.x-specific interface, but I assume you can call any included Java classes directly: http://vertx.io/mods_manual.html
(Interestingly enough, Vert.x uses Gradle for its build/dependency manager, but I guess wanted something more Node-like for its module system)
By using a Java JDBC database driver you're completely losing any async support. Same presumably goes for redis or Mongo drivers. You can do some of the work with threads and pooling, but it's still not the same, and makes this another useless micro benchmark.
What? What do you mean by non blocking in this context?
Well, this is the JVM, not a single threaded javascript engine. As the other guy says below:
"You don't need to necessarily have non-blocking libraries to take advantage of the async I/O. Netty uses worker threads to prevent blocking the server event loop and I assume Vert.X does as well. You can do blocking JDBC queries, Redis, etc."
And threadsafe libs --of which are tons--, usually advertise it on "the box.
Really what you are comparing here is the efficiency of the paths between the two JavaScript engines and their polling I/O libraries, more than any JIT work (and let's face it, even if we were comparing JIT work, the Sun JVM has had a lot more time to tune and tweak than V8 has). In Node's case, it's talking through libuv, which means it has to transition in-and out of the V8 engine's runtime and in to a C runtime. Even if the C code is super zippy, that's costly. For Vert.x though, all the I/O and polling is integrated in to the runtime/VM/JIT. That's kind of nice.
An interesting way to test what I'm suggesting would be to do the same test with unix domain sockets/named pipes as the transport instead of TCP. The JVM doesn't have a native implementation, so it'd have to call out through JNI. I'd wager even odds it ends up slower than TCP on localhost.
Better write a Mongo-backed fibonacci generator to check.
nodejs beats Vert.x for example. People shouldn't be so quick to accept these half thought out microbenchmarks.
I don't think these are speed tests.
Just number of connections that can be handled
These benchmarks are nothing but speed tests.
Javascript yes. Node.js, not so much.
>There have been other server-side JavaScript frameworks in the past, but none of them have taken off like Node.js.
Javascript was not a fast language in the past, nor was it much used for anything more than the most basic dynamic html stuff (rollovers etc)...
I remember a time when my colleagues who were steeped in C++ had a good laugh at my expense because I was building server-side web applications with a new framework and a hot, new language. It woefully under-performed similar C++ applications in benchmark tests.
It was 1998, and the language was Java. I could write my applications much faster and in a more maintainable way than they could, but they didn't care. Their technology was proven, and Java was simply a fad.
I have a hard time believing the JVM is really 10x faster than v8 for such a simple server.
Any benchmark you care to look at should clearly shows JVM is much faster: http://shootout.alioth.debian.org/u64/benchmark.php?test=all...
Honest question, why?
There should be a larger application that even remotely resembles some kind of real world usage. Maybe some day we'll have some kind of a "standard" for a web framework benchmark, an application that actually does something so it's worth benchmarking.
This micro-benchmark makes sense. It's benchmarking an HTTP server essentially. Any benchmark further than this would really be benchmarking the JVM and V8. While that would be interesting, I think in this case, this micro benchmark is OK as long as you know its limitations.
The reality is that most people's app code and databases are going to bottleneck long before either Vert.x or Node.js do. The main thing this benchmark clears up is that both of them are really, really, fast, and that if you do lots of simple to process responses you may want to go with Vert.x.
Kind-of true. But to give any results that can be applied to the real world, it would have to use a much larger payload than a hello world.
http://blog.yafla.com/Pet_Store_2011__Metrics_Instead_of_Eva...
These micro-benchmarks aren't even a good kicking off point for comparisons, as the things that yield a trivial benchmark win are often the things that yield significant performance troubles at scale.
Node is a joy to use because of the NPM, and all the available libraries. I'd hate to lose that.
That said, so long as it has a solid websocket api, and I can do routing in it like I would express, I'd give this framework a shot
Maven's not bad at all (from a consumption perspective--from a dev perspective, it's a bit of a pain in the ass), and it looks like pretty much any Java library that doesn't do anything too insane should work just fine. (Disclaimer: never used vert.x myself, but I did a quick scan of the code.)
However, it's unlikely that node modules will work as is with Vert.x, since the API is different. (Unless someone writes a translation layer)
On the blog post about version 1 being released it mentions being able to mix and match several programming languages. Does this mean you can use different libraries written in different languages in the same Vert.x server?
Might be nice to also see a FAQ about the differences between vert.x and Play 2
At some volume though, you want to do what the grandparent recommends -- front your application server with nginx, apache, or something. Otherwise serving up static assets is taking away resources that should be spent on the application. Consider if you have a page with 5 images, 5 JS files and 5 CS files for each page created. That means you're serving 15 static assets for every 1 dynamic asset you'd really want to use Node for. While Node can still be "good enough", it is not spending its time doing the stuff you really want to use it for in the first place. A dedicated piece like nginx goes much further.
And also use a CDN :p
https://gist.github.com/2652991
and then I get the following results:
vert.x:
39890 Rate: count/sec: 3289.4736842105262 Average rate: 2958.1348708949613 42901 Rate: count/sec: 2656.924609764198 Average rate: 2936.994475653248 45952 Rate: count/sec: 3277.613897082924 Average rate: 2959.610027855153
node.js:
38439 Rate: count/sec: 4603.748766853009 Average rate: 4474.62212856734 41469 Rate: count/sec: 4620.4620462046205 Average rate: 4485.278159589091 44469 Rate: count/sec: 4666.666666666667 Average rate: 4497.515122894601
Making that change so they both store the file in memory and nodejs is 50% faster than vert.x.
This is using an m1.small instance on EC2, and both vert.x and nodejs only using a single core.
And artificially crippling Vert.x to a single core does not prove anything. Anybody who cares about performance will be using more than one core.
I doubt the requests number too. Writing a dummy socket server (evented, threaded, ...) that just returns "HTTP/1.1 200 OK" will not get you anywhere close to 120k requests/sec. The system call becomes the bottleneck.
I.e from request to corresponding response and how many of those it can do per second.
If you doubt the numbers please feel free to run them yourselves, all code is in github
Or would a response that is sent 30 seconds after the request came in contribute to the metric too?
If you're worried about your programs containing rogue & misbehaving code like this, I recommend you use https://github.com/isaacs/nosync
Results vary a little but all way below the Vert.x results.
See blog post for the stats.
I believe servlets are still the most scalable web stack out there.
So I would think that given a heavy load on a many-core machine with interesting enough computations, nothing could beat servlets' performance.
I've seen my share of web servers which are very different in their compliance.
Also file IO are heavily cached by the OS. You can bet that one file is read from memory most of the time. Disk IO is pretty much out of the equation.
https://gist.github.com/2650401
Even with os caching there is still quite a bit of overhead there. Would be interesting to see the benchmarks run on the corrected code:
People in the B community come out in outrage saying that the testing is flawed, that microbenchmarking is useless, that this and that. Rinse and repeat.
