Use case

Time-series with FFT

RDM has the capability of generating a C/C++ interface based off of a time series database definition along with creating a matching full set of Fast Fourier Transformation (FFT) API calls. The FFT calls support scaling, absolute value and real computations along with being designed in a modular manner such that a developer can easily swap the Raima FFT library out with any other custom or third-party library to suit their needs. The generated time series code also supports automatic arithmetic, geometric, and harmonic mean calculations along with down sampling and data splitting. 

Aerospace

Aerospace and defense

Live data capture
Post flight analysis
Capture lots of data
Reliably store data
Process data in real-time
Replicate data to the cloud
Securely communicate data
Low compute
High data volumes
Backlogged data not lost
Automotive

Automotive industry

Condition monitoring
Capture map data
Reliably store data
Process data in real-time
Use irregular information
Store alerted information
Merge sensor and map data
Triggers / Actionable
Industrial

Industrial automation

Condition monitoring
Live data capture
Capture sensor data
Reliably store data
Process data in real-time
Talk to other devices
Light footprint
Low compute
Triggers / Actionable
Backlogged data not lost
Healthcare

Healthcare

Inventory management
Capture lots of data
Reliably store data
Retrieve & process data
Use irregular information
Store alerted information
Replicate to storage
Triggers / Actionable
Energy

Energy & natural resources

Condition monitoring
Live data capture
Capture sensor data
Reliably store data
Process data in real-time
Use irregular information
Store alerted information
Low compute
Light footprint
Triggers / Actionable

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