Although this may sound like an inefficient process compared to simply managing memory manually, the GC incorporates various optimization techniques to reduce the time an application is frozen while waiting for the GC to complete (known as pause time).
The most important of these optimizations is one that makes the GC generational. This technique takes advantage of the fact that while many objects tend to be allocated and discarded rapidly, certain objects are long-lived and thus don’t need to be traced during every collection.
Basically, the GC divides the managed heap into three generations. Objects that have just been allocated are considered to be in Gen0, objects that have survived one collection cycle are considered to be in Gen1, and all other objects are considered to be in Gen2.
When it performs a collection, the GC initially collects only Gen0 objects. If not enough memory is reclaimed to fulfill the request, both Gen0 and Gen1 objects are collected; if that fails as well, a full collection of the Gen0, Gen1, and Gen2 objects is attempted.
Many other optimizations are also used to enhance the performance of automatic memory management, and in general a GC-based application can be expected to approach the performance of an application that uses manual memory management.