Is it scalable, yes, if you scale can there be surprise bills, yes. Is it a capable system, mostly.
I agree with the other answer, it depends. If you are just starting and want a quick way to stand up something and get an MVP out and prove it is viable, use it. But just build your product with the foresight that it isn't probably where you want to base yourself forever. Don't lock yourself into firebase only features etc.
We use it today (for an MVP) and are moving off it for the final product, not necessarily because of surprise bills or major problems but because data security and industry requirements don't accept Firebase as secure. To be fair, I'd move off it either way, as it isn't a great backend to be on for an enterprise application IMO. But for getting something up and testable, sure, it is quick, and pretty easy to prototype with.
5 comments
[ 0.31 ms ] story [ 19.5 ms ] threadWhat are you planning to use it for and how big are your datasets?
Is it scalable, yes, if you scale can there be surprise bills, yes. Is it a capable system, mostly.
I agree with the other answer, it depends. If you are just starting and want a quick way to stand up something and get an MVP out and prove it is viable, use it. But just build your product with the foresight that it isn't probably where you want to base yourself forever. Don't lock yourself into firebase only features etc.
We use it today (for an MVP) and are moving off it for the final product, not necessarily because of surprise bills or major problems but because data security and industry requirements don't accept Firebase as secure. To be fair, I'd move off it either way, as it isn't a great backend to be on for an enterprise application IMO. But for getting something up and testable, sure, it is quick, and pretty easy to prototype with.
I would use whatever you know and not try to add new learning in unless you absolutely need to.