By nature, industrial facilities consist of physical assets and processes that evolve through time. Therefore, each data point generated by such systems is essentially a snapshot of events at that particular point in time.
By extension, this data wants to be stored in a way that reflects the sequential order of events, so that it can be rapidly queried and analysed, among many other reasons.
But yet, this isn't a capability that is inherently baked into the more common Relational and NoSQL databases. Hence the rise in popularity of Time-Series Databases for industrial Telemetry Data storage over the past few years.
At the forefront of this revolution is InfluxDB, an Open-Source Time-Series Database platform developed by InfluxData.
To understand how Time-Series Databases work, and InfluxDB in particular, I had a chat with Brian Gilmore who is the Product Manager for IoT at InfluxData.
Check out our full conversation in the video linked below.
Outline:
✔️ Characteristics of IIoT Data
✔️ Why Time-Series Databases Matter for IIoT
✔️ Common IIoT Use Cases for Time Series Database
✔️ How to Plan an IIoT Data Architecture
✔️ InfluxDB Time-Series DB Platform
✔️ InfluxDB - Open Source vs Cloud vs Enterprise
✔️ InfluxDB Time-Series DB Migration
✔️ InfluxDB Deployment Options
✔️ Acquiring Industrial Telemetry Data into InfluxDB
✔️ Industrial Telemetry Data Enrichment in InfluxDB
✔️ InfluxDB Integration with Analytics & Visualisation Platforms
✔️ Factory-Floor to InfluxDB Data Pipeline
Ep 03: Fundamentals of Edge Computing - Rob Tiffany ( VP & Head of IoT STrategy - Ericsson )
Ep 02 : Principles of IIoT Architecture - Rick Bullota (Co-Founder, Thingworx)
Ep 01 : The Ultimate Guide to Digital Twins - Pieter van Schalkwyk (CEO, XMPRO)
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