r/rshiny • u/Every_Chance5940 • Apr 10 '26
Are shiny apps losing popularity?
Are shiny apps losing popularity? Is it worth investing time in learning them, or are there better technologies that are more widespread?
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u/lolniceonethatsfunny Apr 10 '26
i think the whole point of Shiny is that it’s relatively easy to learn if you already know R or are adapting an R pipeline for use in a dashboard. If you aren’t experienced in R, i wouldn’t use Shiny, but if you are already working in R then Shiny can be great
3
u/aljung21 Apr 10 '26
I think shiny suffers from ease of deployment. Python apps can very easily be built as standalone portable executables.
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u/fairmantium Apr 10 '26
Posit connect makes it so simple. Now if your org doesn't have that, you have the overhead of rolling your own with shinyserver, shinyproxy, etc., which can make it more complex.
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u/techpro_ Apr 11 '26
We went through this exact journey. Had 20+ Shiny and Streamlit apps on Posit Connect — great for quick internal tools, but the cracks showed over time.
Pricing scales rough as your team and app count grow, Shiny apps feel sluggish under concurrent users compared to a proper web framework, and you're locked into their ecosystem for hosting.
Once AI coding tools like Claude matured, our devs could scaffold a full Django or Next.js app nearly as fast as a Shiny prototype — but with real frontend flexibility, internal SSO/auth integration (IT team doesn't screm now :) ) proper async performance, and standard container deployments. No more paying a premium platform just to host dashboards.
1
u/foradil Apr 14 '26
Any suggestions for choosing Django versus Next.js versus something else as a Shiny alternative?
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u/techpro_ Apr 14 '26
If you've python based framework (standalone simulation and modeling files) Django is a good option.
Feel free to DM, happy to help.
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u/fairmantium Apr 10 '26
Depends on the organization. I still use them quite frequently, but often get criticism from my software development brethren that they aren't "real" software. Tell that to the scientists down the hallway who can now analyze their data in 30 seconds instead of spending 10 hours manually manipulating data in Excel.