SingleStore computing data at scale

We are proud to say that SKAI is a data company and our main asset is our data. My department handles the Measurements data and other incoming data sources. SingleStore is used across the organization to do real-time calculations, supply fast loading grids and store massive amounts of data. In our department, users needed to configure pre-hand MetaData for the calculations that they are basing their decision on. Our nightly batches used to work extremely hard and waste valuable time and resources to make this data available the next day (while storing it both in raw form and aggregated) and any changes required a rerun of the batch. Today the clients can configure, change and get their aggregated data in almost real-time, while the data is being stored in SingleStore only in its raw form. It allowed us to add more calculations and more data and use fewer resources on our server-side and the added bonus is that our clients love it!

We don't use it as a predictive analytics tool (at least not in my teams).

Scaling wasn't easy in MemSQL. It improved recently. We are mainly using it to bring in more and more data without affecting performance.