My experience has been that if the execution stays inside the VM, then for a "server side" application, the JVM is faster, and proportionally even faster when there are more threads ready to do something.
When the VM has to do a lot of interaction with the OS, then I think it is difficult to make general statements about Java vs Python, because there is so much dependency on how a particular library interacts with the operating system or with a remote server. For example a database driver which is doing a lot of conversion between the data representation of the database and the native representation of the VM may chew up more time than anything else, and for CPython that driver may be doing all that stuff in a C library where the Java version of the driver may be doing it all in the JVM and taking an order of magnitude longer. It seems to me like the guts of the JVM and CPython VMs are pretty comparable in terms of performance, and both languages are amenable to taking advantage of the performance of the VM. Other than the library implementations for interfacing with the outside world, for me the major performance distinction is with concurrency. I tend to implement solutions which rely pretty heavily on shared objects and the java.util.concurrent facilities, and it seems to me like the CPython VM is not able to easily provide the level of simple clean shared object concurrency support the JVM does. And my experience with the Python "multiprocessing" module is that while it is better than nothing, it does not seem to facilitate nearly the level of efficient shared object support the JVM does. -- http://mail.python.org/mailman/listinfo/python-list
