Why isn't some big company putting its weight behind Julia considering what it has to offer in the field of data science? I just don't get why it's still playing second fiddle to Python. Tech is full of inertia, paradoxically.
They aren't as big as Python because Python has been around for nearly 30 years. Julia is just a baby compared to that. As it grows it will increase it's share. It may not ever surpass Python in terms of raw users, because Julia is focused on numerical computing, but Python is more general purpose.
That isn't the case. Julia's primary focus is scientific/numeric, but it's also general purpose. Take a look at Julia Robotics, for instance:
You could call any Turing-complete language with I/O a general purpose language, but some are clearly designed for certain tasks.
Same as J
> Tech is full of inertia, paradoxically.
I don't think it's paradoxical. Novelty is essential in academia, but that is not the case in industry.
2. Over concentration of the main contributors within the same startup that has a questionable business model and long-term prospects
3. Language issues that limit the desirability of Julia for use in larger projects
Depending on what you're doing, Python is usually great at performance where the time it saves the user writing code is more valuable than the performance itself (a lot of exploratory scientific research).
I can tell you that programmer productivity can plummet drastically when you need to get everything into vectorized form.
Also, custom classes and types do not vectorize well at all.