How to Get More from Your Data Historian Without Replacing It
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Summary
Data historians were built for plant-level SCADA historization, and for that job, they still work. But every new sensor, site, or analytics initiative exposes the same limitations: per-tag costs that spiral as you scale, siloed architectures that can't consolidate across sites, and proprietary interfaces that block your data science and analytics teams entirely.
In this live demo, we will show how InfluxDB 3 fills that gap. Purpose-built for high-frequency industrial telemetry, with unlimited cardinality, native SQL, and flexible deployment across edge to cloud. No tag budgets. No proprietary SDKs. No integration tax.
We'll cover:
- Live technical demo: We'll simulate a multi-site industrial deployment—temperature, pressure, vibration sensors streaming using InfluxDB, Python Processing Engine and Grafana.
- Architectural patterns for historian augmentation or replacement
- Direct comparison of legacy historian capabilities vs. InfluxDB 3 for high-frequency industrial workloads
Speakers
Cole Bowden
Developer Advocate
InfluxData
Cole Bowden is a Developer Advocate at InfluxData, where he helps the Influx community learn how to best use InfluxDB. With six years of experience in the data space, Cole is an expert in data analytics and databases, and he was previously a software engineer at Meta. You can always find him on the InfluxDB Community Slack or on Discord as datacole.
Ben Corbett
Solutions Engineer
InfluxData
Ben Corbett is a Solutions Engineer at InfluxData. He has been working in the real-time solutions space since graduating with a 1st class Masters from the University of Bath in Mechanical Engineering, putting his love for connecting the digital and physical worlds into practice through developing many IoT platforms and real-time applications across the Energy, Manufacturing, Agriculture, Construction, Smart Building, and Electric Vehicle sectors. Since joining InfluxData, Ben has worked with our EMEA and APAC customers to understand and demonstrate the value of InfluxDB as applied to their specific use case or time series challenges.
