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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.

PlatformsMicrosoftIBMAmazonOpen SourceGE PredixGoogle Cloud
Device SDKAzure IoT Device SDK,
Connect
TheDots.io
IBM Watson IoT Platform Client Library,
Watson IoT Platform Device recipes,
Paho Library
Device SDK for AWS IoTPaho Library, Cyclon.js, and many other optionsPredix MachineMQTT Client
Protocol SupportedHTTP,
AMQP
MQTT
MQTT,
HTTP
MQTT,
HTTP
MQTT, AMQP, HTTP etc.MQTT,
HTTP
MQTT,
HTTP
Core platform – IoT Messaging platformIoT 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 RedshiftCassandra (or alternatives like MongoDB)Asset Data,
Time Series,
Redis,
Postgre
SQL,
Blobstore
Time Series,
Cloud Bigtable
Analytics platform – Real-time StreamingTime Series Insights,
Microsoft Stream Analytics
IBM Analytics Engine,
IBM Streaming Analytics
AWS Glue,
Amazon Kinesis
Apache Spark StreamingAnalytics
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 handlingNotification Hubs, PowerBIEmbeddable Reporting, IBM Push NotificationsAWS 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 ComputingAzure IoT EdgeIBM Edge Application ManagerAWS IoT Greengrass CustomPredix EdgeEdge 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.

Tags : iot-guide
Navveen

The author Navveen