Jython - is it faster to use Python data structures or Java ones?
The point of using Jython is that you can write Python code and have it run on the JVM. Don't ruin that by making your Python into Java. 
If -- if -- it turns out that your data structure is too slow, you can drop-in replace it with a Java version. But that's for the optimisation stage of programming, which comes later.

I guess I should try to answer your question. I would guess that using native Java structures will be faster (because the JVM can infer more about them than the Python interpreter can), but that might be counterbalanced by the extra processing needed to interface with Jython. Only tests will tell!
I'm trying to understand whether and under what circs one should use Python classes and/or Java ones.  
If making a specialist dictionary/Map kind of class, should one subclass from Python's dict, or from Java's HashMap or TreeMap, etc.?
It is tempting to use the Python ones just because they are simpler and sexier.  But one reason that Jython runs relatively slowly (so it appears to me to do) seems to have something to do with the dynamic typing.  I'd better say I'm not that clear about all this, and haven't spent nocturnal hours poring over the Python/Jython interpreter code, to my shame.
Anyway it just occurs to me that the Java classes might possibly run faster because the code might have to do less work.  OTOH maybe it has to do more.  Or maybe there's nothing in it.  Anyone know?