Any data written to the database must be valid according to all defined rules, including constraints, cascades, triggers, and any combination thereof.
This does not guarantee correctness of the transaction in all ways the application programmer might have wanted (that is the responsibility of application-level code) but merely that any programming errors cannot result in the violation of any defined database constraints.
[1] In a distributed system, referencing CAP theorem, consistency can also be understood as after a successful write, update or delete of a Record, any read request immediately receives the latest value of the Record.
It is defined variously as: As these various definitions are not mutually exclusive, it is possible to design a system that guarantees "consistency" in every sense of the word, as most relational database management systems in common use today arguably do.
"[7] In the CAP theorem, you can only have two of the following three properties: consistency, availability, or partition tolerance.