Making Sense of IoT Platforms: AWS vs Azure vs Google vs IBM vs Cisco

The growth in connected devices over the 2015–2025 decade. Source: IoT Analytics

IoT architecture layers

  • perception layer (hardware components such as sensors, actuators, and devices),
  • transport layer (networks and gateway),
  • processing layer (middleware or IoT platforms), and
  • application layer (software solutions for end users).
How an IoT system works.

Perception layer: IoT hardware

Transport layer: networks and gateways

Processing layer: cloud middleware or IoT platforms

  • connectivity or ensuring smooth data streaming and interactions between all IoT components;
  • device management, which enables you to control and configure each piece of hardware in the IoT network as well as update software running on devices and gateways;
  • data management, including data collection, processing, and storage;
  • data analysis for extracting valuable patterns with machine learning, predictive analytics, and other methods;
  • visualization or displaying data findings in the form of charts, graphs, 2D or 3D models;
  • digital twin or creating the virtual representation of a device;
  • IoT app development — platforms provide a workspace with a set of tools and templates to speed up app designing; and
  • edge / fog computing — the practice of processing and storing data on devices, microcontrollers, gateways, and other IoT nodes to reduce burden for cloud servers.

Application layer: software solutions for users

IoT platform landscape and key players

The largest target areas for IoT platforms. Source: IoT Analytics
Top five solutions for building IoT.

AWS IoT Platform: the best place to build smart cities

AWS IoT infrastructure. Source: AWS

AWS IoT Core

Additional AWS IoT control services

AWS IoT Analytics

  • Amazon QuickSight, a business intelligence service to visualize data insights,
  • Jupyter Notebook that provides powerful tools for machine learning and advanced statistical analysis, and
  • Amazon SageMaker, an environment for building, training, and deployment of machine learning models.

Edge computing stack

Cisco IoT: the edge computing leader with the largest fleet of connected cars

Cisco IoT Control Center

  • machine learning. The Control Center analyzes 3 billion events a day to improve connectivity management, identify anomalies, and proactively address issues, increasing security.
  • eSIM as a service. This tool simplifies SIM portability between different operators worldwide. The eSIM service allows for creating the local profile of a SIM card embedded in an IoT device — instead of building complex integrations between different service providers.
  • 5G readiness. The platform already supports 5G non-standalone (NSA) resting upon the existing 4G infrastructure. By the end of 2020, the company is going to add 5G standalone (SA) indicationg the creation of a new separate network.

Cisco Kinetic IoT operations platform

Edge computing stack

IOx environment structure. Source: Cisco Blogs

Google Cloud IoT: driving transportation with Google Maps

Google Cloud IoT Core

  • Cloud Functions to create independent functions and instruct devices how to react on specific events,
  • Cloud Dataflow to preprocess data in real time,
  • Cloud Bigtable to ingest and store large volumes of data,
  • BigQuery to analyze data in real time, create and train machine learning models,
  • Data Studio to visualize insights extracted from BigQuery, using pre-built templates, and
  • Cloud Datalab to develop custom analytics practices and visualizations.
Cloud IoT Core integrations. Source: Google Cloud

Edge computing stack

IBM IoT suite: bringing intelligence to fields and factories

IBM Watson IoT Platform

  • device management service to add and remove devices individually or in bulk, perform rebooting, update firmware, receive metadata, and so on,
  • safe connectivity and communication between devices based on MQTT protocol messaging; and
  • data lifecycle management, which enables you to store data from devices and access real-time and historical data whenever you need it.

Digital Twins

Digital Twin components. Source: IBM Developer

IBM Edge Application Manager

Microsoft Azure IoT: ahead of the pack in healthcare and security

Azure IoT Hub

  • device-to-cloud messaging;
  • device authentication;
  • support for HTTP, MQTT, and AMQP protocols; and
  • device monitoring and diagnostics.
  • cloud-to-device messaging,
  • device management,
  • device and module twins or storing information about the current and desired properties of devices and their components (modules), and
  • IoT Edge to create program modules and deploy them across the network nodes.

Azure IoT Central

Additional IoT services

How to choose the best IoT platform

  • high scalability, fitting the needs of any business, from startups to enterprises with millions of devices;
  • built-in security for every layer of an IoT system; and
  • tech support and detailed documentation on their products.

Pricing and free tier

What will it cost to run IoT?

Hardware compatibility

Domain expertise



Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store