A time series database is specifically about being able to store the same information over time and then being able to quickly aggregate that information. This is very common in IoT because typically you have data coming in from all the different sensors, and those sensors are reporting that data, usually on some type of interval (maybe it’s every minute or every hour or whatever the case is), and it’s the same information each time but it has a different time stamp. So the time series database – you could technically store a time series in any kind of database – but that is specifically designed to be very efficient at storing the same information over and over again with a different time stamp on it. It’s very efficient at being able to aggregate that data so you can say well, I have rainfall data from every ten minutes over the last week but I want to know quickly how much rainfall we had in the last week. A time series database is very good at aggregating that and giving us the count – the rainfall data for the week as opposed to the data from hundreds of different samples. A time series database is purpose-built and very common in IoT because IoT by its very nature is all about collecting data over time and reporting the aggregated data to the user. Other database technologies just don’t do this very efficiently. A time series database, because it is such a common requirement for IoT applications, is one of the capabilities that’s built into Prism.
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