[formerly_proven]

I used to believe in these database antipatterns (e.g. avoid EAV, avoid attribute tables, avoid denormalization, avoid overnormalization, avoid inheritance, avoid wide tables, only use synthetic keys, only use natural keys, never use autoincrement, always use autoincrement), but these days I'm almost certain all of them are wrong, because they are independent of business domain needs. Business domains have antipatterns for their data, data in general decidedly does not. For example, storing physical addresses is subject to a number of antipatterns, including stuff like "natural keys are not a good idea for this".

GP cited EAV as an antipattern, yet it is one of the most reasonable approaches to user-defined fields (especially when suitably augmented), which are frequently a business requirement.

[andrewingram]

Not even just user-defined fields, any time where the fields need to be defined as data values rather than part of your concrete data model. Product attributes on a big multi-category e-commerce site being another example. You could just stick them in JSON, but it's still essentially EAV, just with a different storage mechanism.

Another advantage of EAV as a pattern, is it makes it straightforward to add metadata to values, like "where did this value come from?". For systems with audit trails, just having keys and values isn't enough.

EAV wouldn't be the first tool I'd jump to -- I've definitely seen it go wrong -- but it feels like it's going too far to call it an anti-pattern.