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copied!<p>If writes are very rare compared to reads (a key assumption in most key-value stores, and not just in those;-), then you might prefer to take a time hit when you need to update scores (a write) rather than to get the relative leaderboards (a read). Specifically, when a user's score change, queue up tasks for each of their friends to update their "relative leaderboards" and keep those leaderboards as list attributes (which do keep order!-) suitably sorted (yep, the latter's a denormalization -- it's often necessary to denormalize, i.e., duplicate information appropriately, to exploit key-value stores at their best!-).</p> <p>Of course you'll also update the relative leaderboards when a friendship (user to user connection) disappears or appears, but those should (I imagine) be even rarer than score updates;-).</p> <p>If writes are pretty frequent, since you don't need perfectly precise up-to-the-second info (i.e., it's not financials/accounting stuff;-), you still have many viable approaches to try.</p> <p>E.g., big score changes (rarer) might trigger the relative-leaderboards recomputes, while smaller ones (more frequent) get stashed away and only applied once in a while "when you get around to it". It's hard to be more specific without ballpark numbers about frequency of updates of various magnitude, typical network-friendship cluster sizes, etc, etc. I know, like everybody else, you want a perfect approach that applies no matter how different the sizes and frequencies in question... but, you just won't find one!-)</p>

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