Meh, this isn't a useful benchmark.
For one, a lot of the code looks like "Java written in X", which just doesn't work.
The Python examples definitely suffer from the above. No one competent in the language would write code like that. They're allocating globs of memory for no reason, and then throwing it away without ever using it. You wouldn't use Django's JSON serializer -- it's known to be very slow. It only exists for people with older versions of Python. You'd use the JSON serializer found in the standard library, instead. There's a few other glaring mistakes, as well.
The Go examples also suffer from similar problems. In fact, it wouldn't surprise me if most of the other languages do. That said, almost all the bottlenecks were seen in the libraries, all of which are standard libraries written in C, so interpreter vs compiler vs JIT made very little difference.
The problem with these kind of benchmarks is they use "throw away" code, and only take part of the equation into account, arguably the wrong half. You have to know your application intimately and benchmark using data which is realistic for that application. This benchmark falls well short of the mark.