I have a multithreaded app writing and reading a ConcurrentLinkedQueue, which is conceptually used to back entries in a list/table. I originally used a ConcurrentHashMap for this, which worked well. A new requirement required tracking the order entries came in, so they could be removed in oldest first order, depending on some conditions. ConcurrentLinkedQueue appeared to be a good choice, and functionally it works well. A configurable amount of entries are held in memory, and when a new entry is offered when the limit is reached, the queue is searched in oldest-first order for one that can be removed. Certain entries are not to be removed by the system and wait for client interaction. What appears to be happening is I have an entry at the front of the queue that occurred, say 100K entries ago. The queue appears to have the limited number of configured entries (size() == 100), but when profiling, I found that there were ~100K ConcurrentLinkedQueue$Node objects in memory. This appears to be by design, just glancing at the source for ConcurrentLinkedQueue, a remove merely removes the reference to the object being stored but leaves the linked list in place for iteration. Finally my question: Is there a "better" lazy way to handle a collection of this nature? I love the speed of the ConcurrentLinkedQueue, I just cant afford the unbounded leak that appears to be possible in this case. If not, it seems like I'd have to create a second structure to track order and may have the same issues, plus a synchronization concern.