Source: thenewstack.io
Data Modeling: Part 2 — Method for Time Series Databases
Read https://thenewstack.io/data-modeling-part-1-goals-and-methodology/ Indeed, the temporal aspect exacerbates the complexity of the modeling task, making simple diagrams look pretty complex.
Instead, if the relationship has no time-varying attribute itself, we extend the tagset of the series modeling the time-varying side with additional tags representing the static side key and an additional tag representing the static entity name.
In some cases, it is convenient to extend our conceptual modeling by transforming the time-varying relationship between the static entities into a time-varying entity with relationships with static entities.
Therefore, by using a continuous query language like Flux, it is possible to represent time-varying relationships across time-varying entities.
Instead, if the relationship has no time-varying attribute itself, we extend the tagset of the series modeling the time-varying side with additional tags representing the static side key and an additional tag representing the static entity name.
In some cases, it is convenient to extend our conceptual modeling by transforming the time-varying relationship between the static entities into a time-varying entity with relationships with static entities.
Therefore, by using a continuous query language like Flux, it is possible to represent time-varying relationships across time-varying entities.
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