In the Data Foundation-project; there is an understanding that times series data will be represented in accordance with OPC-UA data model using the FDM (DM) functionality in CDF. Is there any issues here in relation to the limitations in FDM stating that there is a limit of 10 million instances? Or will it be designed so that this will not be an issue?
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Scalability issues with representing time series data in accordance with OPC-data model using FDM (Data modelling)
Best answer by Kjetil Halvorsen
OPC-UA can carry various data “types”, and depending on which type of data you are sourcing via OPC-UA, you may want to leverage different resource types / capabilities in CDF.
In simplified terms, we can make the following, high-level guidance:
- Structural entity data. This part of the data typically represents the setup of the control system (from which the OPC-UA data is sourced). You could think of this as the equipment and sensor breakdown structure which helps understand the context of sensors and events. CDF Data Modeling is a good destination for this part of the data.
- Data points, sensor values, variables to be tracked over time. This part of the data matches very well with the CDF Timeseries resource type.
- Events. This part of the data matches well with CDF Events (primarily), or Data Modeling (secondarily).
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