Quote from: SatoNatomato on March 21, 2017, 10:23:48 AM

Dont you have more important things to do, such as updating the accounting book, I mean, the database of IOTA?

Do you have a better counterargument?

Quote from: escapefrom3dom on March 21, 2017, 11:04:06 AM

quote from the source:

CAP is frequently misunderstood as if one had to choose to abandon one of the three guarantees at all times. In fact, the choice is really between consistency and availability for when a partition happens only; at all other times, no trade-off has to be made.

Sorry, didn't bother to read the actual article. Try https://www.infoq.com/articles/cap-twelve-years-later-how-the-rules-have-changed:

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In its classic interpretation, the CAP theorem ignores latency, although in practice, latency and partitions are deeply related. Operationally, the essence of CAP takes place during a timeout, a period when the program must make a fundamental decision-the partition decision:

cancel the operation and thus decrease availability, or

proceed with the operation and thus risk inconsistency.

Unless you put all 12 witnesses on a single machine you have to deal with the following situation:

Blue balls are picked by 4 witnesses as the main chain, green balls are picked by other 4 witnesses and there is another version picked by the remaining witnesses (it's not shown to emphasize that noone can have a complete view of the DAG). Under high load every witness will pick its own main chain because none of them will see the whole DAG. The chance of that is high because

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In normal use, people mostly link their new units to slightly less recent units, meaning that the DAG grows only in one direction.

is not true in high load, the DAG becomes very wide.