I would not mind quoting the Druid documentation for this purpose: “Druid is a data store designed for high-performance slice-and-dice analytics (“OLAP“-style) on large data sets. Druid is most often used as a data store for powering GUI analytical applications, or as a backend for highly-concurrent APIs that need fast aggregations.”
You might be wondering where is “SQL” in that? Actually, the fact is Druid is designed for special kind of SQL workloads which we can relate with powering the GUI analytical applications which require low latency query response. But in this post, we will only look in the “how part” of it using Druid to quickly run queries.
Click through to see how.