These are what i'd say, as someone who has tinkered with it a lot but uses python/C++ for $day_job: - immature web/network services stack. For better or worse

These are what i'd say, as someone who has tinkered with it a lot but uses python/C++ for $day_job: - immature web/network services stack. For better or worse the lang seemed to focus on more number crunching throughput early than reliable distributed data processing, but the latter is a much larger market and what most enterprises care about. It's the difference between a lang only having Matlab or R ceiling vs python-like ceiling. - poor static compilation or static analysis story. this is what a lot of people needing to put code in production need. It's also standard expectation now with a lot of dynamic language code (python or js) that aims to be in production. - for certain types of realtime uses, more direct control of memory is doable, but you have to jump through hoops. Again, determinism is very important. - historically, compile times were quite horrid. part of this was llvm, part of it was julia. It's gotten way better in 1.6 and 1.7, but compilation results need to be cached more than just precompilation. however, all being said, I love the lang! There is a lot going for it especially how the package ecosystem works. There is also a lot of innovative projects.