The memory usage is in part by stuff like BLAS that you can drop if you know how to, and probably mostly about Julia having an excellent optimizing compiler, and the price you pay is more memory use. Interpreted languages, or Python (actually has a compiler now by default, just simpler) inherently use less memory.
On my machine idle Julia 1.6 rc1 takes 0.5% of memory (down from 0.6% for older Julia) and it seems like a good trade-off. This is with 32 GB RAM (I had to downgrade my machine from 128 GB… strangely my Supermicro wouldn’t boot). If you only cared about memory use, you would use older Python2 or even better Perl which has lowest mem (and fastest startup):
$ ps aux |grep julia
pharald+ 4098 22.3 0.5 1636904 187208 pts/14 Sl+ 19:38 0:01 /home/pharaldsson_sym/julia-1.6.0-rc1/bin/julia --startup-file=no
pharald+ 4228 34.8 0.6 749156 203908 pts/14 Sl+ 19:41 0:01 /home/pharaldsson_sym/julia-1.5.1/bin/julia --startup-file=n
pharald+ 4269 0.2 0.0 27428 8928 pts/14 S+ 19:43 0:00 python3
pharald+ 4391 0.0 0.0 21060 4576 pts/14 S+ 19:48 0:00 perl