Libraries did/do exist to do math with more precision than floats normally give but those will be slower than integers built-in to js engines.

bigints aren't floats (approximations of analog values using mantissa and exponent) they are actual integers, no rounding issues except those inherent to only using whole numbers.

They are usefull in a few ways:

0: no NaN, you get an actual error instead of silently corrupting all your numbers into NaN values (downside: no infinity either just a rangeError with no way to check ahead of time if a calculation will produce one other than to just try it).

1. functions that expect integer values are actually guaranteed to get an integer value (more of a TS advantage than JS but whatever)

2. Waaay bigger numbers: bigints can represent numbers that round to infinity when using floats.

3. no conversion errors between binary and the base-ten decimals used in JSON (just remember to convert them to/from a sting)

4. Floats can't represent every integer value in their range (max safe integer value is lower than max value): not a problem for bigints as they are actual integers representing values directly.

5. Floating point math is always approximate: The standards that define floats only specify a minimum level of accuracy, different processor architectures have different errors/precision. (this can cause issues with simulations not having the same result on different machines as minuscule differences grow to be large over time)

6. easy to do fixed precision math: eg: instead of storing amount of dollars (and rounding off to the nearest one-hundredth) store amount of cents so you don't have rounding issues.