Top 10 IIoT Platforms

There are many vendors in the industrial IoT platform marketplace, offering remarkably similar capabilities and methods of deployment. And not one of them has differentiated itself enough at this point to be a clear leader in an emerging market.

Gartner’s June 2019 Magic Quadrant for Industrial IoT Platforms, for example, has no Leaders or Challengers. And its 2018 report, the first Magic Quadrant to look specifically at IIoT platforms, said there was no “dominant provider.”

With a high volume of platform options for industrial businesses to consider, we set out to identify a shortlist to make the task of choosing an IIoT platform easier.

Given the fractured and crowded market, and the growing potential of IIoT to extract value from data, reduce costs, improve operations and present new business models, analysts recommend that businesses looking for a platform devote time to research. They also suggest focusing on industry-specific use cases and outcomes.

“We are seeing more of a vertical specialization in all IoT platforms,” said Ian Hughes, senior analyst for IoT at 451 Research. “But use cases are driving the application layer.”

Prime use cases in manufacturing are production monitoring and inventory management, he said. In oil and gas, the use cases are supply chain optimization and worker safety. And many IIoT use cases relate to core overall operational efficiency (OEE), equipment monitoring and predictive maintenance because “any downtime is extremely costly,” Hughes said.

Simply put, IIoT platforms create a vital, single view of an operation. Their function is a “superset” of an IoT platform in that it shares common core functions, according to Hughes. “IIoT platforms have to integrate with a wide range of legacy manufacturing equipment and protocols, and some of the equipment can be many decades old or more but still core to operations.”

IIoT platforms also differ from legacy operational technology (OT) in industrial environments. They provide more cost-effective collection of higher volumes of high-velocity, complex machine data from networked IoT endpoints. IIoT platforms integrate siloed data. They improve insights through specialized data analysis and enable actions, and they improve data visualization.

For industrial enterprises, “the unrealized promise” of IIoT is to marry the strengths of OT and IoT for “enhanced data acquisition, condition monitoring and superior analytics,” according to Gartner. “Together, these combined offers will augment and eventually replace legacy control systems.”

According to industry analysts, an IIoT platform should provide:

• Device management software that connects thousands to hundreds of thousands of sensors, industrial machines and digital systems. IIoT solutions are usually designed to identify failures and facilitate recovery from failure.
• Integration through software development kits, development tools and APIs to support business processes and enterprise systems across the business. There are significant challenges, however, given the array of back-office applications such as ERP, application performance management, enterprise asset management, computerized maintenance management systems and more.
• Data management to control and monitor ingestion, storage, accessibility, flow and
• Analytics of data from connected devices, the enterprise and third parties to reveal patterns and optimization of assets.
• The enablement and management of applications to simplify configuring and operating connected assets and that enable digital twins.
• Software to allow security audits and ensure compliance, including measures to prevent data loss and to detect and act on breaches.
• Support for protocols relevant to the industrial domain, such as OPC (Open Platform Communications) Unified Architecture.
• Engineering-level robustness to prevent downtown.
• Flexibility with no-code interfaces, for example, to allow a range of users to access job-specific applications.
• A combination of cloud computing, on-premises deployment and edge computing.

Using compute and analytics at the edge is quickly becoming the de facto approach to managing data, according to Gartner, which predicts that by 2022, there will be more IIoT analytics performed at the edge than analytics on “cold” data stores in the cloud.

An IIoT platform should also be able to orchestrate functions such as machine learning, using edge computing, as the volume of time-series data in some forms of manufacturing is too great to transfer to the cloud, Hughes said. Also, the latency required to act upon the data such as in safety or critical situations is too long in the cloud.

Another challenge to full-cloud deployment comes from the industrial organizations themselves and the culture of engineers that “places high trust in what they can touch and control,” according to Gartner, which expects that 30% of industrial enterprises will have full, on-premises deployments of IIoT platforms in 2023, up from 15% this year.

To help readers make a choice among IIoT platforms amid rapidly evolving technology and capabilities, we compiled a list of the top products in this space. Our list focuses on a company’s maturity, size, history of experience with industrial software and the breadth of use case scenarios. We also took into consideration high rankings from analysts who specialize in IIoT verticals.

Here’s the list of the top 10 products in the IIoT platform space, which is presented alphabetically (registration required):