The usual wisdom in clr-land is that the generational garbage collector can cope just fine with a lot of small, short lived objects. It absolutely doesn't like big, long lived objects that reach G1, G2 or the large object heap and must be traversed for a full gc.
This means that normally, you want to avoid data structures that introduce a lot of objects trees, linked lists and stuff like that. In some circumstances you might lose some speed, but win big time when the full GC comes. Additionally, It may be worthwhile to consider avoiding heap allocations by organizing your data as value types instead of ordinary objects.
It depends on your definitions of "a lot" is. It can scale pretty high by default, but when you're doing hundreds of millions of objects in a short window, you can actually measure pauses in the app domain while GC runs. These have a pretty decent impact on requests that hit up against that block.
The vast majority of programmers need not worry about this, but if you're putting millions of objects through a single app domain in a short time, then it's a concern you should be aware of. This applies to pretty much any managed language.
Are you sure that this is really because of Gen0 collections all by themselves, and not because the short cadence of collections leads to a lot of premature Gen1 promotions? I could imagine something like
var a = InitGiantArray<Foo>();
var b = InitGiantArray<Bar>();
could leave you with a lot of foo garbage in Gen1 or even Gen2, right were it really hurts. On the other hand I'd be surprised if something akin to
do {
Tuple.Create(new object(), new object());
} while (true);
but with something useful thrown in would suffer much under GC pauses. Looks like I have to test it :I)
This means that normally, you want to avoid data structures that introduce a lot of objects trees, linked lists and stuff like that. In some circumstances you might lose some speed, but win big time when the full GC comes. Additionally, It may be worthwhile to consider avoiding heap allocations by organizing your data as value types instead of ordinary objects.