For sure. We didn't pick 10^10 scaling. It's just what some massive brokerages/exchanges actually use. The fact that these were not necessarily crypto made us take note.

At the same time, you can understand that 10^10 scaling is at least significantly more precise. And I can imagine these things are viral too, who you trade with, also determines your minimum resolution. You can always downsample in presentation, but once downsampled in storage, it's impossible to upsample.

It also wasn't the only use case. But it tipped the scales.

Some languages do have proper support for ratios, so if you define x = 22/14, the value stored is 11/7. Multiply later by 7 and you get 11.

You can maintain exact calculations through an entire data pipeline this way, as long as your base numbers are all integers and ratios, and optionally have one rounding step at the end if you want a decimal value. Most math languages and lisps do this.

There must be libraries for other languages that can do it too, but it’s much nicer to work with when it’s built-in.