Wanted to get some opinions from folks here that have actually built and shipped with Electron.
Background: Building an API IDE on Electron. Designing this to not be “just an API client”or a thin wrapper around a webapp. It’s a pretty original desktop tool with a lot of editor/IDE-like behavior: local workflows, richer interactions, and some things that I think would have been much harder to build and maintain in a more constrained setup. So yeah, thats why we went for Electron.
this is the tool: github.com/voidenhq/voiden :)
Now, as adoption is growing, we are starting to get the usual questions about memory footprint and app size.
The (slightly) frustrating part is that when the app is actually being used, the app-side memory is often pretty reasonable. In many normal cases we are seeing something like 50–60 MB for the actual usage we care about (even added it in the app itself for people to check it out).
But then people open Activity Monitor, see all the Chromium/Electron-related processes, and the conversation immediately becomes:
“yeah but Tauri would use way less”
And then, without realizing, I suddenly end up talking and philosophizing about Electron, instead of discussing the tool itself (which is what I am passionate about :)
Of course Electron also has overhead. Pretending otherwise would be foolish. So we are constantly optimizing what we can, and we will keep doing so…
At the same time, I do feel that a lot of these comparisons feel weirdly flattened. For example people often compare:
full Electron process footprint VS the smallest possible Tauri/native mental model
…without always accounting for development speed, cross-platform consistency, ecosystem maturity, plugin/runtime complexity, UI flexibility, and the fact that some apps are doing much more than others. Which is by the way the reason that we went with Electron.
So all this context to get to my real question, which is:
How do you explain this tradeoff to users in a way that feels honest and understandable, without sounding like you are making excuses for Electron?
And also, for those of you who have had this conversation a hundred times already:
What do you say when people reduce the whole discussion to “Electron bad, Tauri good”?
Have you found a good way to explain footprint in practical terms?
Mostly trying to learn how others think about this , especially those who have built more serious desktop products and had to answer these questions in the wild.
built and open sourced a postman alternative, and decided to do it on Electron.
what has been funny is indeed when having to "defend" electron when it comes to memory footprint etc.
One thing that I always thought was interesting is that people make the argument by comparing the full Electron process footprint VS the smallest possible Tauri/native mental model and all without thinking about all the advantages of electron like development speed, cross platform consistency etc.
we have now optimized it a lot and we even show the actual usage inside the app for folks to monitor.
with my team we built Voiden for some of these reasons, initially for our own internal use (building many APIs for our SaaS marketplace). Most of the folks in the team have been postman power users before so we do remember the time when this was indeed something new.
Problem now is that most of the alternatives out there (including the ones you mentioned) do offer some great things but essentially they feel variations of the same concepts - so I see them as "Enshittification on the way". Reason we built voiden is that we wanted something that challenges these ideas. You can try it out and let me know if it resonates: https://github.com/VoidenHQ/voiden.
apologies for the slight promo - but based on your comment I thought it might be relevant.
Today I released the community plugins for Voiden.
This is a big one because one of the things I dont want is the API tool to become bloated with new features - so I want to allow anyone to build plugins to grow the tool.
Not sure if “code has always been expensive” is the right framing.
Typing out a few hundred lines of code was never the real bottleneck. What was expensive was everything around it: making it correct, making it maintainable (often underestimated), coordinating across teams and supporting it long term.
You can also overshoot: Testing every possible path, validating across every platform, or routing every change through layers of organizational approval can multiply costs quickly. At some point, process (not code) becomes the dominant expense.
What LLMs clearly reduce is the short-term cost of producing working code. That part is dramatically cheaper.
The long-term effect is less clear. If we generate more code, faster, does that reduce cost or just increase the surface area we need to maintain, test, secure, and reason about later?
Historically, most of software’s cost has lived in maintenance and coordination, not in keystrokes. It will take real longitudinal data to see whether LLMs meaningfully change that, or just shift where the cost shows up.
one of the creators here - you are right in the sense that most tools start open source and then they close source. For us it was different/ the opposite. We first made it as a product and then we open sourced it. It was never our intention to make it a SaaS though nor charge for it.
well void is also the blank slate in the sense that Voiden is a tool without rules - without explicit directions to the users on how they should do xyz. So yeah, our inspiration comes from an empty sheet, a blank slate to work with APIs. And if there are no restrictions then there are infinite opportunities. :) thts how it makes sense to us.
Voiden: Released the Voiden Runner so that users can test APIs directly in the terminal. https://github.com/VoidenHQ/voiden
ApyHub: https://apyhub.com/ working to onboard a few more API providers. Working to rationalize the terms for new APIs added in the catalog.
I am also working to streamline how all APIs are certified and monitored.