Much of the manipulation of large data sets today involves significant computations, often performed in certain stylized ways. However, traditional database query languages do not provide support for such computations, requiring them frst to fetch data from the database and then manipulate it outside. Where such manipulations are data intensive, it has been shown in many contexts that performing the manipulation within the database itself is more efficient. It can also relieve the application programmer of the burden of specifying the algorithms for these manipulations.

The MauveDB paper studies two frequently used computational operations -- regression and interpolation. It provides a mechansim to specify each within the database, with the result being a "view" that the application programmer can use. The expected performance improvements are demonstrated experimentally. There is much still to be done, in terms of better access mathods for such selected new operators, better integration with the standard query optimization techniques, identification of additional such operations, and so on. What this paper does is open the gates to a new area of research, into which I hope others will follow. For doing so, this paper merits both attention and credit.