I used to work at a data analysis startup called Jut. Jut’s vision was to bring all your data together in a single environment. This enabled integrated analysis using our programming language, Juttle. It was challenging because there are many different types of data. Different data types require different models for optimal storage and querying. At the highest level, Jut divided all data into two kingdoms: metrics and events. Today I’ll cover the design and implementation of the metrics side, which was covered by a database named Orestes that we built.
Historical note: This was originally published as a post on Jut’s blog. Nobody wanted to pay for the product it describes, so Jut has gone in a very different direction of late, and Jut’s blog is a 404 at the moment. As a technical piece, though, I think it merits keeping alive.