Even though not all Internet of Things solutions require a platform in order to perform its functions, for most of them platforms could be very beneficial. Thus, we would like to cover the most popular of them in this digest and describe how they differ from each other.
Amazon is definitely among the most popular cloud providers as well as AWS Internet of Things platform among other solutions. It provides a complete toolkit for developing any Internet of Things products. It allows you to built on a scalable, secure, and proven cloud infrastructure and scale to billions of different devices and trillions of messages. It consists of device software (Amazon FreeRTOS, AWS IoT Greengrass), control services (AWS IoT Core, AWS IoT Device Management, AWS IoT Device Defender, AWS IoT Things Graph) and data services (AWS IoT Analytics, AWS IoT SiteWise, AWS IoT Events). Meanwhile, it enables multi-layered security and allows to build superior AI integrations for your Internet of Things solution. AWS offers you a pay-as-you-go approach for pricing for over 120 cloud services. With AWS you pay only for the individual services you need, for as long as you use them, and without requiring long-term contracts or complex licensing.
Unlike AWS, ThingWorx is a specially dedicated platform for building Industrial Internet of Things applications and perhaps is the most robust platform in this realm. It has a broad set of features, including multiple connectivity options, application development tools, analytics, and AR (built around a single, real-time view of a physical object) allowing to create scalable IIoT solutions fast. ThingWorx also supports cloud and edge analytics and different deployment options.
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Obviously such an innovative tech giant as Google offers its own Internet of Things toolkit that allows connecting, processing, storing, and analyzing data both at the edge and in the cloud, providing reliable and secure storage of data. The platform includes scalable, fully-managed cloud services; an integrated software stack for edge/on-premises computing with machine learning capabilities. The pricing model is built on pay-as-you-go principles. It requires no upfront costs and no termination fees. Most common platform use cases are predictive maintenance, real-time asset tracking, logistics and supply chain management, and smart cities, and buildings.
This is an platform offering from one more tech pioneer – Microsoft. It consists of a wide network of various applications performing different functions like real-time data stream processing, pushing notifications, multi-model database, predictive analytics, AI, etc. You can easily select the ones you need for your particular use case. By the way, the platform can support a large number of devices and has high reliability. As to the pricing, it has a complex licensing model that depends on the number of devices, number of messages, features and many other facets.
IBM Watson IoT platform usually associates with strong Artificial Intelligence and Machine Learning background. Besides AI functionality, the IBM platform supports effective remote device control, secure data transmission, and storage in the cloud, real-time data exchange, etc. It manages risk and security by governing applications and devices within an Internet of Things ecosystem: usage and performance patterns, anomaly detection, data, and transaction validation. It also enables quick and easy parsing, filtering, and transforming device and performance data.