JavaScript speed is heavily overrated. This is a Web 2.0 myth.
Let me explain this claim a bit (and don't just downvote me for saying something you do not want to hear!)
Sure, JavaScript V8 is a quite highly optimized VM. It does beat many other scripting languages in naive benchmarks.
However, it is a very limited scope language. It is meant for the "ADHS world" of web. It is a best effort, but it may just fail and you have little guarantees on things completing or completing on time.
Consider for example MongoDB. At first it seems to be good and fast and offer a lot. Until you see for example that the MapReduce is single-threaded only and thus really slow. It's not all gold that shines!
Now look at data mining relevant libraries such as BLAS. Basic linear algebra, math operations and such. All CPU manufacturers like Intel and AMD offer optimized versions for their CPUs. This is an optimization that requires detailed understanding of the individual CPUs, way beyond the capabilities of our current compilers. The libraries contain optimized codepaths for various CPUs all essentially doing the same thing.
And for these operations, using an optimized library such as BLAS can easily yield a 5-20x speedup; at the same time matrix operations that are often in O(n^2) or O(n^3) will dominate your overall runtime.
So a good language for data mining will let you go all the way to machine code!
Pythons SciPy and R are good choices here. They have the optimized libraries inside and easily accessible, but at the same time allow to do the wrapper stuff in a simpler language.
Have a look at this programming language benchmark:
http://benchmarksgame.alioth.debian.org/u32/which-programs-are-fastest.html
Pure JavaScript has a high variance, indicating that it can do some things fast (mostly regular expressions!) others much slower. It can clearly beat PHP, but it will be just as clearly be beaten by C and Java.
Multithreading is also important for modern data mining. Few large systems today have a single core, and you do want to make use of all cores. So you need libraries and a programming language that has a powerful set of multithreading operations. This is actually why Fortran and C are losing popularity here. Other languages such as Java are much better here.
