One question that we'd like to have a more concrete answer to is, "How does TorqueBox perform compared to project X?" In a quest to answer that question I enlisted the help of the community and started benchmarking TorqueBox against Trinidad, Unicorn, Passenger, and Thin for some simple applications. If you're unfamiliar with these servers, TorqueBox and Trinidad run under JRuby while Unicorn, Passenger, and Thin run under MRI.

Obviously most applications are not as simple as those used for this initial benchmark but our goal was to understand TorqueBox's baseline performance so we can compare performance across releases and make realistic claims regarding where we stand relative to the alternatives.

Setup

All applications, results and installation instructions are stored on GitHub to be as open as possible. You'll also find the exact command used to run each server for each test and any other specific details or comments about the individual tests under the results/ tree. All the tests were run against an Amazon EC2 m1.large instance so anyone should be able to reproduce these results by starting their own instances and running the tests.

Results

Rack Hello World

Source Raw Results

This is an extremely simple Rack application that just prints "hello world". The test is designed to see how quickly each server can respond to Rack requests.

10 Clients

100 Clients

Comments

As you can see above, TorqueBox leads the pack with Trinidad and Thin not far behind and Unicorn and Passenger bringing up the rear.

The slope you see at the beginning of the graphs with JRuby vs MRI servers is interesting. The JRuby servers definitely have a warm-up period before they start running at full speed and I'm not entirely sure why - if I had to guess I'd say it's related to JIT compilation of the code.

Rack Sleep

Source Raw Results

This test is identical to the Rack Hello World test except every request sleeps for 100 milliseconds before responding. This is designed to simulate a request blocking on an external resource (database, cache, http). Experimentation showed each server performed best when started with at least as many workers as concurrent clients.

100 Clients

With the exception of Thin, all servers have similar performance with 100 concurrent clients. I'm not sure why Thin's performance was so low but it was excluded from higher client loads of this test since it wasn't able to perform adequately.

250 Clients

The remaining servers continue to perform well at 250 concurrent clients. The number of requests per second each was able to handle increased as expected with the increased client load.

500 Clients

I was not able to start Passenger with a max pool size of 500 so it was omitted from the final sleep test. Unicorn, however, had no problem managing 500 workers and continued to perform well but lagged behind the JRuby servers.

Comments

The above tests were also done with Passenger and Unicorn using a more typical number of workers (10 - 20) but both performed substantially poorer than with a number of workers equal to the number of concurrent clients. This makes sense because the majority of the time spent servicing each request is sleeping and not using the CPU.

This test is designed to mimic a real-world use-case but also favors JRuby since spinning up a few hundred threads is much less resource-intensive than a few hundred processes.

Rails Hello World

Source Raw Results

This is an extremely simple Rails application that just prints "hello world". The test is designed to see how quickly each server can respond to Rails requests.

10 Clients

Comments

Unlike the Rack Hello World test, the test server was CPU-bound with just 10 clients and tests with higher loads yielded very similar results with no appreciable increase in overall requests/second.

Trinidad and TorqueBox are substantially ahead of the other servers. I'm a bit surprised that Trinidad outperforms TorqueBox in this test when TorqueBox outperforms Trinidad in the Rack tests - I'm sure there are some optimization opportunites here.

Rails Fibonacci

Source Raw Results

This test is designed to be very CPU-intensive by calculating the Nth Fibonacci number on every request.

10 Clients

Comments

These results are very similar to the Rails Hello World results and I think it's because both tests ended up being CPU-bound with just 10 concurrent clients. Higher concurrent client loads didn't increase overall requests/second.

Next Steps

I'm pleasantly surprised with TorqueBox's speed given that we've spent almost zero time working on performance. Because our Rack performance is so good, there's probably some low-hanging fruit on our Rails side of things to bring that performance back in line with Trinidad.

None of these benchmarks actually talked to an external resource like a cache or database because I wanted to concentrate on web server performance specifically. In the future I'd like to also incorporate some tests that store and retrieve data from memcached and a database to look for any performance gains or losses under JRuby and TorqueBox specifically.

We welcome any and all feedback on the benchmarks and encourage you to fork and fix speedmetal if you encounter any issues reproducing our results!