Summary: Python isn't the bottleneck yet, and if it becomes one, C will become the last 1%.

I've been working on production apps in Python since 2002, including ones doing large-scale compute running 1000+ machines at once. How: 99% python, 1% C. But the trick is, you only build in the C once you've worked out all the kinks and optimized the big-picture stuff elsewhere. Python is great for not only connecting things, but rapidly iterating on algorithms and building maintainable code.

The AI / ML community has discovered this too: Python is now the most popular language in that community. Despite the heavy compute. How: most of the popular libraries have efficient C (etc) implementations under the hood.

This is exactly the philosophy we've been following at BigchainDB, with success. Python to connect things, iterate quickly in improving algorithms, and ship maintainable code. We haven't got far enough to resort to building our own C libraries yet, though many 3rd party libraries we use are implemented in C.

[EDIT] Based on the comments below, I'll now mention here too: BigchainDB wraps MongoDB, which is written in C++. And, Python 3.5+ (which BDB uses) has gradual typing, which brings many benefits of static typing to Python.