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4. How do your device applications need to process real-time data? *

Store data with high density (e.g. 120 Hz per stream)

Filter, aggregate, or merge high-density data as it arrives

Communicate data to other devices with minimum lag

Sample data is averaged over time before it is transmitted or stored on the device

Data is filtered, e.g. to identify outliers, before it is transmitted or stored on the device

Data that arrives with varying lag or out of order delivery must be reordered by time

Data from multiple sources is combined and correlated on the device before it is transmitted or stored

Other

5. How do your device applications access historical real-time data after it is stored on a device?

Export data in large batches (e.g. daily, weekly, or annually)

Answer remote queries from other devices

Search for individual data points by timestamp

Calculate statistics over a long time period (e.g. mean, min, max, standard deviation)

Search for full-resolution sample values over a long time period

Search for patterns across multiple sample values captured over time

Search for keywords in large documents

Easy to learn, prototype before any coding, benefit from flexibility to scale with MCU/MPU compatibility, and more