IoT project development: reviewing top 7 IoT platforms

7 min readNov 13, 2017

Today, analysts expect IoT revolution in many life spheres and business industries. According to recent predictions, by 2020 there will be over 26 billion connected devices worldwide!

Coming up with intelligent connection of everything, the Internet of Things promises to transform the world, changing the way we work, live, and entertain.

Since IoT provides the ability to automate workflow, monitor and manage various things, collect and process data, now we see a significant rise in IoT solutions, with a wide range of use cases, advantages, and opportunities.

Concerning IoT project development, effective device connectivity, security issues, IoT expertise, and up-to-date technologies take the center stage. Also, there are some challenges to take into account.

Check out whether companies should invest in the Internet of Things despite security risks.

Challenges with IoT project development

Systems are overwhelmed by huge data volumes, including continuous increases in data amounts
There is a wide range of Internet-connected devices, all of them are to be successfully interconnected
Data streams must flow both in and out of devices
Large data sets are required to be safely stored, querying, and managed
Application scaling and deploying issues

What is IoT platform

IoT platforms appeared to solve various challenges with the Internet of Things. Simply put, an IoT platform is mainly about connecting IoT devices and applications and filling the gap between device network and sensor arrangement.

By using backend applications and analytics tools, an IoT platform enables data storage and processing capabilities with making sense of large data volumes collected by multiple IoT devices.

As IoT technology attracts a lot of attention and huge investment, there is a plenty of IoT platforms providing the ability to develop, deploy, and scale IoT applications.

IoT platforms

1. Microsoft Azure IoT Suite

Like other corporations interested in IoT technology, Microsoft works hard on delivering successful tools and technologies for building advanced IoT projects. Microsoft Azure IoT Suite platform provides a wide range of services allowing to create, customize, and deploy IoT solutions.

Azure IoT Suite is a complex platform mainly introduced by:

Supported protocols: HTTP, AMQP, MQTT
Data management tools: Cosmos DB, Microsoft SQL, Azure Storage
Monitoring and analytics tools: Azure Stream Analytics
Analytics, machine learning: Azure ML
Data visualization and management tools: Notification Hubs, Power BI
Monitoring and management features: IoT Hub, Event Hubs

Stream Analytics provides intelligent data analytics and incoming telemetry processing capabilities. Also, Stream Analytics enables to perform aggregation and deliver informational messages to other services.

Microsoft Cosmos DB, Microsoft SQL, and Azure Storage ensure secure data storage and management, while Power BI tool is responsible for data visualization through interactive dashboards and tables.

Azure IoT Hub is used for device management and cloud-device messaging. Representing an important platform service, it also provides both device-to-cloud and cloud-to-device messaging.

2. IBM Watson IoT

IBM Watson IoT is a cloud-hosted platform, allowing to connect multiple IoT devices and manage the entire IoT landscape. The platform provides many capabilities that include collecting, analyzing, storing, and communicating data.

Watson IoT platform involves the following elements:

Supported protocols: MQTT
Data management tools: IBM Watson IoT Platform
Monitoring and analytics tools: IoT Real-Time Insights, IBM Streaming Analytics
Analytics, machine learning: Predictive Analytics service (on Bluemix) + SPP Modeler (offline)
Data visualization and management tools: Embeddable Reporting, IBM Push Notifications
Monitoring and management features: IBM Watson IoT Platform

What’s important, IBM Watson IoT allows remote device monitoring and management, data visualization via interactive dashboards, real-time analytics. Also, it enables to enrich IoT applications with natural language processing and other capabilities.

3. AWS IoT

AWS IoT (by Amazon Web Services) is an automated cloud platform that enables connected devices to safely interact with IoT applications and other devices. AWS IoT platform provides secure data storage and data management capabilities, including remote device monitoring and cloud-device messaging.

Speaking about platform components, AWS IoT includes:

Supported protocols: MQTT, HTTP, WebSockets
Data management tools: Amazon DynamoDB, Amazon Redshift
Monitoring and analytics tools: Amazon Kinesis
Analytics, machine learning: Amazon Machine Learning
Data visualization and management tools: AWS Lambda, Amazon QuickSight, Amazon Simple Notification Service
Monitoring and management features: AWS IoT

The device SDK supports such programming languages as JavaScript, C, and Arduino and involves client libraries, a developer guide, and a migration guide for manufacturers.

AWS IoT platform provides SDK for reliable and quick connection of both devices and applications. Also, it enables message exchange with AWS IoT via MQTT, HTTP, and WebSockets protocols.

4. GE Predix IoT

General Electric’s Predix is a purpose-built cloud Industrial Internet of Things (IIoT) platform, that perfectly suits for building, deploying, scaling, and managing industrial IoT applications.

GE Predix provides smart industrial intelligence helping to create innovative business models, generate new revenues, and making true value from IoT data. Comprising a wide range of tools and features, Predix combines asset modeling, big data processing, and machine learning capabilities.

GE Predix is mainly introduces by the following elements:

Supported protocols: MQTT ,WebSocket, HTTPs
Data management tools: Asset Data, Time Series, Redis, PostgreSQL, Blobstore
Monitoring and analytics tools: Analytics Runtime
Analytics, machine learning: Custom Analytics Support (Python, Java, MATLAB)
Data visualization: Mobile SDK, Dashboard Seed
Monitoring and management features: RabbitMQ

The platform provides a rich industrial-grade analytics library and framework to deliver advanced machine learning analytics. Also, with Predix you can ensure effective data management, from data collection and storage to data processing and visualization.

5. Google Cloud IoT

With the end-to-end platform, Google provides the ability to connect multiple IoT devices, receive advanced analytics, accelerate business, and improve decision-making. For today, Google Cloud IoT is among the most popular IoT platforms in the world, enabling users to reduce costs and deploy IoT applications.

Check out Google Cloud IoT platform elements:

Supported protocols: MQTT, HTTP
Data management tools: Cloud Storage, Cloud Bigtable, or Cloud Spanner
Monitoring and analytics tools: BigQuery
Analytics, machine learning: Cloud Machine Learning
Data visualization and management tools: Cloud Data Studio
Monitoring and management features: Cloud IoT Core

IoT Core represents a completely managed service and an essential platform component, enabling users to easily connect and manage devices and applications, collect and analyze data in real-time. What’s more, IoT Core helps ensure security and establish safe communications.

Using Google Cloud IoT platform, you get advanced intelligent analytics thanks to BigQuery, receive simple data visualization feature with Cloud Data Studio, and derive intelligence with the help of Cloud Machine Learning.

6. Confluent Open-Source

Confluent Open-Source provides various capabilities. Like all large platforms, Confluent allows effective device connectivity, data storage and exchange, and intelligent data processing and management. Being the only platform built entirely on Apache Kafka, Confluent is a great choice for making sense from IoT data.

Apache Kafka is a distributed streaming platform offering reliable responses to support customer-facing applications and connect various systems with real-time data. Launched by LinkedIn in 2011 and representing a scalable messaging queue, Kafka soon grew up to a mature streaming platform. For now, it provides not only publish-and-subscribe capabilities, but also secure data storage and data processing within real-time streams features.

Confluent Open-Source include the following components:

Supported protocols: MQTT, AMQP, HTTP
Data management tools: Cassandra (or such alternatives as MongoDB)
Monitoring and analytics tools: Apache Spark Streaming
Analytics, machine learning: Apache Spark MLlib
Data visualization and management tools: Custom, Zeppelin (dashboards)
Monitoring and management features: Protocol Bridge, Apache Kafka

Also, Confluent involves clients that enable Kafka cluster to interact with applications written in a wide range of languages including Java, C/C++, .NET, Python, etc.

The Kafka Connect API enables simple and reliable connection to leading data system and allows the creation of custom connectors as well.

7. Murano

Murano by Exosite is an advanced cloud-based IoT platform allowing to build, deploy, and manage connected devices and applications. Murano enables more simple and reliable device connectivity as well as safe data storage and management.

Murano platform is primarily introduced by:

Supported protocols: an industry-standard TLS protocol
Monitoring and management features: Gateway Engine
Data visualization: Dashboard Builder
Device SDK: The ExositeReady Embedded SDK
Development libraries for: C, C++, Python, Java, .NET, Node, Go, etc.

Murano provides a powerful engine allowing to collect and process real-time data. Also, the platform includes embedded support for device status management, firmware updates deployment, and more.

By using a device connectivity layer, programmers get the ability to easily connect multiple devices and communicate data via various encrypted connections.

Several tips for choosing an IoT platform

When choosing an IoT platform, pay attention to the entire technological sphere. Keep in mind that the Internet of Things has a wide range of use cases in different industries and even different companies.

For a manufacturing company it can be introduced by embedding sensors in the workshop equipment. For an insurance company it includes installing telematic sensors in the cars of insurance policyholders. For example, GE Predix is a great choice for developing industrial IoT applications.

Then, it’s important to consider the ability to receive data and prepare it for analysis: the platform must be able to effectively process and manage multiple high-speed data streams from a variety of different sources.

Pay attention to the cloud infrastructure owner. The decision to rely on major IoT platform suppliers like Microsoft, Amazon, or IBM also means using the software, hardware, and cloud infrastructures under their control. Users of relatively small IoT solutions will probably focus on one or a limited group of cloud providers.

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