As for the sparseness argument for plain-text representations: while latency histograms are sometimes (and maybe most of the time) sparse, when they capture large latency events (such as hiccups, pauses, or deep queuing conditions) that sparseness tends to be significantly reduced (when no coordinated omission is in effect). E.g. when a "blip" of 2 seconds occurs in a system that normally serves 10K operations per second, 10K different values between 0 and 2,000,000usec will see recorded counts. A histogram that captures the latency distribution seen during such an event will NOT be sparse, but it will still be highly compressible (since most of those counts will fall in a very narrow integer range. A plain-text representation of counts at non-zero buckets (such as the JSON format you propose) would probably take up 80KB or so, while the compressed histogram will probably still fit in 1-2KB.