Reminds me of IBM Informix TimeSeries which has been around for a while. This was IBM's attempt to bridge the gap between the relational model and the columnar format that is optimal for time series, except that they store the time:value arrays in blobs. Aside from compression benefits the columnar storage works really well for irregular time series. If the incoming data is irregularly spaced, row-based schema will have a certain degree of inefficiency due to the need to store NULLs each time one of the columns is missing a valid value.