Best IoT Platforms & Software

Over a few short years, the Internet of Things (IoT) has evolved from an intriguing concept with limited capabilities into a full-fledged platform for IT and business.

Organization are increasingly turning IoT platforms to perform an array of tasks, ranging from real-time inventory visibility and predictive maintenance systems to energy and smart buildings. They’re also adopting Industry 4.0 tools like digital twins. It’s safe to say that no sector has been left touched by the IoT – cloud computing in particular is linked to IoT.

IoT software plays an important and growing role in connected systems. They introduce an architecture that tames some of the rough edges associated with connecting devices, standards, protocols and software systems. Instead of building an IoT framework entirely from scratch, they tie together device management, data collection, data analytics, machine learning (ML), IT integration and cybersecurity. IoT and Industrial IoT (IIoT) platforms simplify tasks, trims costs and drive performance gains.

Of course, finding the right platform is essential. Pricing models, standards, cloud connectivity and elasticity, system flexibility and security methods vary greatly. Some platforms excel at connecting sensors while others are focused more on communications and data processing.

As a result, it’s important to consider what your organization’s requirements are for hardware, data access, reporting, and budgeting before selecting an IoT platform. Different business models and different IT infrastructures are better suited to one platform or another. 

How to Select the Best IoT Platform

There are several factors to consider when analyzing the IoT platform marketplace. These include:

What are we trying to achieve?

As with any information technology solution, it’s important to start with an assessment of how the IoT can automate and improve business practices and processes. This includes productivity gains, faster and better functionality and lower costs.

What technology do we already have in place?

It’s essential to analyze existing IT, cloud and network frameworks to determine their fit with an IoT platform. Along the way, an organization must determine whether current IoT devices will work with the framework and which, if any, require upgrading, retrofitting or outright replacement.

Is the platform flexible?

The IoT space is evolving at a furious rate. While all these vendors support some level of flexibility, not all approaches are equal and some are a better match for certain IoT configurations. There’s also a need to support a growing array of open source components. Matching your roadmap with theirs is essential.

What type of data analytics and machine learning (ML) does it support?

IoT frameworks are designed to automate data collection and processing on the edge. Machine learning is a key part of this picture. As a result, it’s important to understand whether an IoT platform supports ML.

What security is in place?

The IoT is notoriously weak in regard to cybersecurity. Device manufacturers rely on various standards and approaches, which often results in gaps and vulnerabilities. A platform may provide some help.

What’s the vendor’s strategy and roadmap?

It’s always wise to survey the vendor to determine how it approaches updates, patches, security issues and other factors. Similarly, it’s important to understand how it handles customer support and how it sees the platform evolving.

What’s the cost and the ROI?

It’s vital to consider the initial cost of an IoT platform but also total cost of ownership (TCO) and what type of return on investment it can deliver to your organization.

Here are ten leading IoT platforms:

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Leading IoT Platforms

AWS IoT

AWS IoT is designed to auto-provision, manage and support connected systems from the edge to the cloud. It includes analytics and data management features, tools for integrating devices, and multi-layered security mechanisms such as authentication, encryption and access controls. The focus is on industrial, connected home and commercials applications. AWS IoT integrates with other AWS solutions and components as well as open source frameworks.

Pros

  • Highly scalable cloud infrastructure supports billions of devices and trillions of messages.
  • Highly specialized tools and device software streamline workflows and processes.
  • Offers pay-as-you-go pricing with templates and ready-build solutions for specific industries.
  • AWS has partnerships with top IoT industry vendors, including Ayla, Bosch, Domo, Deloitte, Kinesis, Wipro and Verizon.

Cons

  • Users report that it can be difficult to setup and use.
  • Some users complain that documentation and product support are at times lacking.
  • Debugging software and connections can be a problem.
  • IIoT capabilities are not as fully built out.

Ayla Agile IoT Platform

This cloud-based platform-as-a-service framework supports commercial and industrial solutions suited to a variety of vertical industries, including food services, appliances and manufacturing. Ayla Agile IoT Platform addresses edge connectivity, device management, data aggregation and processing, and enhanced security functions.

Pros

  • Partnerships in place with leading cloud and service providers, including AWS, Google Cloud, IBM and Qualcomm. A cloud connection agent simplifies connectivity and support.
  • Receives high marks for ease of use and the large number of devices it supports.
  • Users report an intuitive user interface (UI) and strong notification and reporting capabilities, including filters and drill-down views of devices.
  • Offers digital twins and advanced diagnostic functions.

Cons

  • Some complain that the platform lacks desired features and capabilities.
  • The focus is on three primary areas: home automation systems, discrete and process manufacturing, and telecoms/Internet Service Providers.
  • May require integration with more advanced solutions to deliver the full functionality required by a business.

Azure IoT

The cloud-hosted platform ties together numerous templates, tools and open source components to support IoT initiatives ranging from condition monitoring to predictive maintenance. Azure IoT Hub manages bidirectional communications to and from devices, including provisioning and authentication. The platform supports numerous industries and use cases, including process manufacturing, energy, healthcare, retail and transportation.

Pros

  • The platform supports hybrid IoT applications through Azure IoT Edge and Azure Stack.
  • Offers built-in device management and provisioning to connect and manage IoT devices at scale.
  • Supports digital twins and offers strong analytics and ML support.
  • Includes a security-enhanced communication channel for sending and receiving data from IoT devices.

Cons

  • Can be complex to set up and use. An extensive knowledge has lots of information about the platform but users report difficulty finding answers.
  • Some users complain that the platform lacks key operational functionality.

Cisco Kinetic

The IoT operations platform handles complex gateway management tasks, including provisioning and monitoring. It also tackles edge and fog processing of data and includes a data control module that facilitates the movement of data using policy enforcement mechanisms. Kinetic supports large IoT deployments and rules-based policy management across multi-cloud environments.

Pros

  • The platform is highly scalable and modular. It can connect a wide-range of devices.
  • Provides deep visibility into nodes, microservices and other components—with a minimal footprint.
  • Strong real-time data visualization with access to various data sources, including IoT devices and databases.
  • Offers pre-built widgets and templates for data visualization and other tasks.

Cons

  • Lacks specialized IoT components that may be necessary for an IoT project.
  • Users report that setting up and using the platform can be challenging.
  • There are some limitations for non-Cisco networking and infrastructure hardware.

Google Cloud IoT

Google Cloud IoT delivers an intelligent platform for building and managing a highly scalable network of IoT devices. It’s designed to manage devices and data on the edge and into the cloud. The platform offers strong analytics, ML and automation features that are valuable for predictive maintenance, real-time asset tracking, logistics and supply chain management and smart city and building initiatives.

Pros

  • Offers a powerful AI platform, including more advanced Vision AI and Video AI that drive insights from images and video in the cloud and on the edge.
  • Offers robust IoT developer kits.
  • Extensive ecosystem of partners, including Accenture, NetApp, Palo Alto Networks, Siemens and Sigfox.

Cons

  • Users report challenges related to setting up, configuring and using the platform.
  • Security and privacy settings can be confusing, especially for APIs and authentication.
  • Limited support for using and importing datasets from outside the Google ecosystem. 

IBM Watson IoT

IBM’s fully managed and cloud-hosted IoT platform delivers a cloud-hosted environment that tackles everything from device registration and authentication to connectivity and data management/analytics. Areas of specialization include enterprise asset management, facilities management and systems engineering.

Pros

  • Highly scalable and flexible.
  • Supports powerful AI-driven analytics and ML functions that can be adapted to an industry or business.
  • Watson cognitive APIs support interconnectivity across devices and vendors.
  • The platform supports blockchain.

Cons

  • Some users report a steep learning curve.
  • Limited data storage formats and options can make global data management challenging. 

Oracle IoT Intelligent Applications

Oracle delivers broad and deep visibility into IoT devices. The cloud-based platform is optimized for smart manufacturing, connected assets, connected logistics, workplace safety and other tasks. It supports the use of real-time data for visualizations, mapping and automation.

Pros

  • Built-in integrations and API framework for ERP, supply chain management (SCM) and other enterprise systems and data.
  • Offers pre-built dashboards and widgets that facilitate deep visibility into data and events.
  • Supports digital twins and 3D visualizations.
  • Offers pre-build threads for enterprise applications such as manufacturing, maintenance, transportations and warehouse management.

Cons

  • Some functions and features are limited to using an Oracle infrastructure.
  • May require third party device management solutions for specialized needs and requirements.
  • Oracle’s IoT Cloud Service doesn’t support a complete range of IIoT protocols and third party IoT products. 

Particle

Particle offers a broad and extensive cloud-to-edge framework for managing connected devices. It accommodates a broad array of tasks, including asset tracking, fleet management, predictive maintenance, environmental monitoring, real-time order fulfillment and remote monitoring and controls.

Pros

  • Global IoT connectivity through Wi-Fi, cellular and BLE in over 150 countries.
  • Strong security features, including built-in device encryption, PKI authentication, robust security logging and strong privacy controls.
  • Strong analytics and ML features.
  • Excellent scalability, including auto-provisioning and device scaling.
  • Large community of users and strong support capabilities.

Cons

  • Complex configurations can be prone to disruptions and interruptions.
  • High upfront costs but these are tempered by reduced operations and development costs.
  • Users complain that the environment can be complex. 

PTC ThingWorx

The ThingWorx platform is a robust and fully developed industrial IoT (IIoT) solutions. It addresses a wide range of manufacturing, service and engineering use cases through end-to-end device auto-provisioning and management. ThingWorx specializes in remote access monitoring, remote maintenance and service, predictive capabilities and other functions on-premises and in the cloud.

Pros

  • Has an extensive global ecosystem of technology partners and systems integrators.
  • Uses more than 150 drivers to boost standardization and connectivity across heterogenous environments.
  • ThingWorx Flow offers powerful orchestration capabilities in a visual environment.
  • Highly rated service and support.

 Cons

  • Users say the digital twin component can be difficult to integrate and use with some industrial applications.
  • Lacks some standardized tools for builds and deployments as well as code analysis and verification.
  • Some users complain about a lack of tools and widgets to manage IoT devices.

SAP Internet of Things

The platform provides cloud, edge and data technologies required to build out the IoT. It also aggregates IoT data to drive analytics, machine learning, and blockchain technologies through SAP Analytics Cloud. In addition, SAP offers various microservices that can be deployed across edge computing and IoT devices. These can be used for smart systems and supply chain optimization.

Pros

  • Strong IoT data management, analytics and ML capabilities. Supports data persistence, streaming analytics, predictive analytics, and contextual features.
  • Supports digital twins through sensor and contextual business data.
  • Strong automation capabilities through IoT application templates.
  • Highly scalable.
  • Top rated service and support.

Cons

  • Users report difficulties integrating components with legacy IT and non SAP components.
  • May require significant customization in order to build out an IoT ecosystem.
  • Some users report difficulties finding features and navigating to desired locations within the platform.
  • Pricing model can be complex.

Best IoT Platform Comparison Chart

IoT Vendor

Pros

Cons

 

AWS IoT

  • Excellent templates
  • Pay as you go pricing
  • Broad ecosystem of partners
  • Debugging can be difficult
  • IIoT capabilities are somewhat limited
 

Ayla Agile IoT Platform

  • Strong partnerships
  • Users find it easy to use with an intuitive interface
  • Strong digital twin support
  • Users would like to see additional features
  • IoT focus is narrower than other vendors
  • May require additional integration
 

Azure IoT

  • Powerful device management
  • Strong digital twin support
  • Focus on security
  • Some users complain about missing features and functionality
  • Can be expensive
 

Cisco Kinetic

  • Scalable and modular platform
  • Delivers deep visibility into devices and microservices
  • Pre-built templates for visualizations and other tasks
  • Implementing and using the platform can be difficult
  • May not support non-Cisco networking components
  • No IoT device hardware offered
 

Google Cloud IoT

  •     Best in class AI, including vision and video AI
  • Robust developer kits
  • Extensive partner network
  • Security and privacy controls can be difficult and confusing
  • Limited support for data residing outside the Google ecosystem
 

IBM Watson IoT

  • Strong support for AI driven analytics and ML
  • Robust APIs support interconnectivity
  • Support for blockchain
  • Some users complain about limited storage options
  • Expensive
 

Oracle IoT Intelligent Applications

  • Build in integrations and APIs
  • Excellent dashboard and widgets
  • Strong support for digital twins and 3D visualizations
  •  Some functions and features aren’t available outside an Oracle infrastructure
  • May require 3rd party device management add-ons
  • Doesn’t support a full range of IIoT protocols
 

Particle

  • Strong security features
  • Highly scalable and flexible
  • Large user community
  •  Expensive
  • Steep learning curve for certain configurations
 

PTC ThingWorx

  • Focus on standardization
  • Powerful orchestration tools
  • Top notch service and support
  • Lacks standardized tools for certain tasks
  • Lack of widgets
  • Expensive
 

SAP Internet of Things

  •  Strong digital twins support
  • Powerful automation
  • Highly scalable
  • Excellent service and support
  • Pricing model can be complex
  • Users say navigation can be a challenge
  • May require heavy customization

 

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