Your options seem to be for SVG output these backends with Plots.jl:
https://docs.juliaplots.org/latest/output/
gr, inspectdr, pgfplotsx, plotlyjs, pythonplot, gaston
You seem to be looking for a workaround for matplotlib, i.e. PythonPlot:
https://docs.juliaplots.org/stable/backends/#At-a-glance
As mentioned you can use PNG not just SVG with it or most backends:
I doubt SVG can be made fast, it’s just inherently scales linearally to be slower, with more points, or even if there’s some workaround, PlythonPlot (and PyPlot) are limited to what matplotlib does (I suppose they support all the features).
Have you thought of using not just a different backend for Plots, rather use Makie? I think it’s going to be the future of Julia plotting, if not already. It has it’s own backends.
I understand the tidier ecosystem is very nice (a go-to by now for people over using DataFrames directly, and not just from people coming from R), and it has:
It uses Makie as its plotting package.
What do you even mean? Different plots, or same plot with both, and editing into one by hand? That seems unworkable, not a scalable solution, if you need to regenerate the plots at least. I at least thought with Plots.jl you choose just one backend, but I suppose you can switch dynamically if it suits you, it’s just seems like a giant hack to be avoided what you are doing.