InfluxDB to Boost Your Ignition Historian

Introduction

Nowaday, data scientists leverage tools like InflexDB for advanced analytics in manufacturing when the use case involve extreme volume of data, cloud use cases. We'll discuss the trade-off to find between on one side, the technical effort required to unlock InfluxDB capabilities and on the other side, the actual payback to address some business needs in manufacturing. There are many prerequisite question to ask. First of all:

• is your IoT platform truly open to these IT tools?
• Then, how to unlock the data communication to InflexDB via REST API or MQTT ?

Let's answer to these question with a sample demo.

Github Tutorial link:

• 💡 Github Tutorial link

Theory vs. Application

The first question to ask: Are you sure your use case can't be solved by a classical historian?

From Native Historians, Platforms like Ignition have inbuilt tools designed to historicize field data (OPC UA) reliably. For standard production monitoring and reporting, these are often more than sufficient.

With InfluxDB, This becomes a "boost" rather than a requirement. It is specifically designed for "extreme volumes of data" and cloud-based advanced analytics that a standard SQL-based historian might struggle to handle efficiently.

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The Integration Effort

A major takeaway from the technical demo is that InfluxDB integration is not native.

The Manual Gap: While a native historian is usually a "checkbox" setup, InfluxDB requires building a communication bridge.
Technical Requirements: You must write scripts to handle REST API communication (specifically HTTP POST requests). You have to decide whether to send data tag-by-tag or in batches (JSON buckets), which requires a developer mindset rather than just a maintenance mindset. If your team lacks these IT skills, the "technical effort" might outweigh the benefits.

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Maturity Threshold

The Starting Point: Most sites should start by simply connecting field devices to an IoT platform and using the native historian. This validates the day-to-day use case.

Expansion: You should only move toward InfluxDB or visualization tools like Grafana once you have reached a "certain threshold of maturity". Pushing for advanced architecture before mastering the basics is presented as a common mistake in IoT strategy.

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