In realtime analytics, a common scenario is that you want to retain a lot of (years of) historical data in order to run analytics over a longer period of time. But these analytical queries occur infrequently and their performance is usually not critical. The bulk of everyday queries, however, accesses only a limited set of relatively fresh data, typically 1 or 2 weeks worth.

With on premise setups, compute/storage separation is often implemented using a NAS or similar storage unit that exposes an S3 API endpoint.

So, you want your realtime analytical queries to be really fast, and that’s why you selected Apache Druid! Today, let’s have a look at another aspect of how Druid achieves its amazing performance.