First of all, any single shopping cart is typically accessed by one single process at a time: the user's browser. I can of course open two or more browser sessions, but this is not a typical use case, it definitely has an upper limit (how many browser tabs can I use concurrently?) and most importantly, lost or duplicated transactions are easily spotted and corrected (you do get plenty of chances to revise your order before paying).
A bank account can be "hit" by different sources at the same time (just think of a company bank account, not just a personal one) and most importantly, duplicated or lost transactions are much harder to prove and rectify.
The browser tabs have an upper limit sure, because on the client/browser side, it just might be unfeasible to open more than 100 tabs realistically.
But, I can assure you, you could open 1000 tabs, and dynamo will be fine, and not lose your data.
You should really read the article I linked, especially the part about vector clocks, it discusses a common approach for dealing with duplicate data, conflicts, and resolution, at scale.
Comments
I am afraid we are comparing apples to oranges.
First of all, any single shopping cart is typically accessed by one single process at a time: the user's browser. I can of course open two or more browser sessions, but this is not a typical use case, it definitely has an upper limit (how many browser tabs can I use concurrently?) and most importantly, lost or duplicated transactions are easily spotted and corrected (you do get plenty of chances to revise your order before paying).
A bank account can be "hit" by different sources at the same time (just think of a company bank account, not just a personal one) and most importantly, duplicated or lost transactions are much harder to prove and rectify.
The browser tabs have an upper limit sure, because on the client/browser side, it just might be unfeasible to open more than 100 tabs realistically.
But, I can assure you, you could open 1000 tabs, and dynamo will be fine, and not lose your data.
You should really read the article I linked, especially the part about vector clocks, it discusses a common approach for dealing with duplicate data, conflicts, and resolution, at scale.