The t-digest construction algorithm uses a variant of 1-dimensional k-means clustering to product a data structure that is related to the q-digest. this t-digest data structure can be used to estimate quantiles or compute other rank statistics. the advantage of the t-digest over the q-digest is that the t-digest can handle floating point values while the q-digest is limited to integers. with small changes, the t-digest can handle any values from any ordered set that has something akin to a mean. the accuracy of quantile estimates produced by t-digests can be orders of magnitude more accurate than those produced by q-digests in spite of the fact that t-digests are more compact when stored on disk.