“At Gold Town Games we have a quite complex, heavily nested operational MongoDB database that is somewhat the developers pride and joy, and because of that it’s not very well suited for analysis. So when setting up an analytic environment we were trying out a lot of different solutions for offloading data from our MongoDB database to our analytic environment at Google Cloud. All the different solutions that we tried failed, this includes Stitchdata, MongoDB BI Connector and more, so we were about to give up and try to squeeze in time to build our own custom solution when we came across SlamData. Due to the history of non existent results we have had so far with vendors for accomplishing our task, it was with quite big amount of skepticism we received the information from SlamData that this should not be any problem due to their unique algorithm. But to our surprise they lived up to their word and now we have a working analytic environment in Google BigQuery on account of SlamData.”
Patrik Berggren – Data Scientist at Gold Town Games AB
MRA defines an elegant unification of structure and identity which allows SlamData to blur the lines between rows, values, structure, and depth. From the standpoint of the mathematics, there is no difference (up to isomorphism) between a pair of values that occur in two separate rows, versus a pair of values that occur in two separate structures within a row. A powerful and unique dependent type system allows us to efficiently compile expressions defined in terms of MRA down to incredibly fast and scalable data transformation pipelines.
You can apply SlamData to data which has tens of millions of rows, or data where each row has tens of millions of values (current row limits allow a maximum of roughly 50 GB per row on a single commodity server or VM), or even data which is both large and wide at the same time! All of these transformations will be evaluated in a streaming fashion with substantially higher performance than hand-optimized Python or even C, not to mention the fact that, with SlamData, you won’t be writing any code whatsoever. MRA powers a sophisticated and intuitive point-and-click user experience for exploring and transforming your data.
MRA lets users work with complex data as it is rather than with some watered-down version. It is a novel and much-needed update of the core algebra that has powered database analytics for well over 40 years.