Comparing IoT Cloud Providers - Azure, IBM, Amazon, GE Predix , Google Cloud and Open Source

This article is part of IoT Architecture Series - https://navveenbalani.dev/index.php/articles/internet-of-things-architecture-components-and-stack-view/

The following table summaries the various capabilities offered by the IoT cloud providers. We had gone through the platform capabilities in this article series.

Platforms	Microsoft	IBM	Amazon	Open Source	GE Predix	Google Cloud
Device SDK	Azure IoT Device SDK, Connect TheDots.io	IBM Watson IoT Platform Client Library, Watson IoT Platform Device recipes, Paho Library	Device SDK for AWS IoT	Paho Library, Cyclon.js, and many other options	Predix Machine	MQTT Client
Protocol Supported	HTTP, AMQP MQTT	MQTT, HTTP	MQTT, HTTP	MQTT, AMQP, HTTP etc.	MQTT, HTTP	MQTT, HTTP
Core platform – IoT Messaging platform	IoT Hub, Event Hubs, Azure IoT Central, Azure Digital Twins	Watson IoT Platform, IBM Maximo (Asset Management)	AWS IoT	Protocol Bridge, Apache Kafka	Rabbit MQ	Cloud IoT Core, Cloud Pub/Sub
Core platform – Database option	DocumentDB Storage (high-performance tables, blobs), Microsoft SQL	MongoDB, Cloudant NoSQL, ObjectStorage, Informix Time Series data, etc.	Amazon DynamoDB, Amazon Redshift	Cassandra (or alternatives like MongoDB)	Asset Data, Time Series, Redis, Postgre SQL, Blobstore	Time Series, Cloud Bigtable
Analytics platform – Real-time Streaming	Time Series Insights, Microsoft Stream Analytics	IBM Analytics Engine, IBM Streaming Analytics	AWS Glue, Amazon Kinesis	Apache Spark Streaming	Analytics Runtime	Cloud Pub/Sub, Cloud Dataflow, BigQuery
Analytics platform – Machine Learning	Azure ML	Watson Studio, SPP Modeler (offline)	Amazon Machine Learning, AWS SageMaker, AWS IoT Analytics, Amazon Lookout for Equipment	Apache Spark MLlib (and other options)	Custom ML Support (Python, Java, MATLAB) + Pre-built industrial analytics and Data science services	Google AI platform, Vertex AI
Alerts and Event handling	Notification Hubs, PowerBI	Embeddable Reporting, IBM Push Notifications	AWS IoT Events, AWS Lambda, Amazon Quick Sight, Amazon Simple Notification Service	Custom, Zeppelin (Dashboards), etc.	Mobile SDK, Dash board Seed	Google Data Studio, Firebase Cloud Messaging
Edge Computing	Azure IoT Edge	IBM Edge Application Manager	AWS IoT Greengrass	Custom	Predix Edge	Edge TPU, Anthos

As mentioned in earlier articles, there are various other complementary services offered by IBM, Amazon, Microsoft and Predix that could be leveraged and used in an IoT solution, like caching, geospatial locations, mobile push events, etc. There might be many more components, which could be used in the above stack, but we listed only those services that provide end-to-end integration in the IoT stack.

From the strategy perspective, all platform providers have the same strategy of providing a set of services to enable development of scalable IoT applications. Clearly, just providing the platform would not provide any unique capability and we would see a lot of tie-ups and partnership from device manufacturers to network providers, open source adopters to start-up’s providing innovative solutions. Apart from partnerships, the real requirement is to develop and provide end-to-end industry solutions on top of the IoT stack as a set of offerings which can be customized based on requirements. For instance, design model of the services used with a connected car solution should not change across car manufacturer. The only thing that would change is device library that is fitted in the car (telematics device) or installed via the OBD port.

With this we conclude our IoT series.