what-is-an-iot-platform

By 2025, an estimated 30 to 40 billion connected devices are expected to be in use worldwide. As of late 2024, over four billion cellular IoT connections. Industries now rely on the Internet of Things (IoT), encompassing everything from industrial systems and smart cities to healthcare and logistics.

As these systems grow in scale and complexity, managing them becomes more challenging. Even small IoT networks can generate massive amounts of data that exceed the processing capacity of edge devices alone. In many cases, real-time responsiveness is essential, regardless of the number of connected devices.

To meet these demands, IoT platforms are becoming critical. They provide the infrastructure to handle complex, data-heavy networks and enable faster, more reliable decision-making across connected environments.

What is an IoT platform?

An IoT system is a network of connected devices that transmit data to the edge or cloud for processing and analysis. These systems rely on four key components: devices, data, connectivity, and analytics.

As the number of connected devices grows, their types diversify, and the demand for real-time analytics increases, managing such systems becomes increasingly complex. That’s where an IoT platform comes in.

An IoT platform is a specialized software layer that bridges connected devices with the cloud. It supports the development, deployment, and maintenance of IoT applications by providing the necessary infrastructure to connect devices, collect and process data, and create applications that interact with these systems.

An IoT platform simplifies the complexity of building and maintaining IoT solutions by handling connectivity, data flow, device management, and security. This allows businesses and developers to focus on the insights and value generated by connected devices rather than the underlying technical challenges.

Types of IoT platforms

Different IoT platforms are built with varying focuses and offer unique functionalities and services. Based on their primary purpose and the services they provide, IoT platforms can be categorized into the following types:

Device management platforms. These platforms manage connected devices throughout their lifecycle, including provisioning, setup, configuration, monitoring, firmware updates, diagnostics, and maintenance. They typically offer features such as device registration, configuration, firmware upgrades, remote diagnostics, and security for devices and data. They’re often integrated with broader IoT platforms, but their primary responsibility is to ensure optimal operation and functionality of devices. Popular examples include Particle and Balena.
Connectivity management platforms. These platforms manage device connectivity, particularly cellular or LPWAN (Low Power Wide Area Network) connections. Their features include SIM management, device activation, network selection, and data transfer optimization. They help maintain stable, efficient communication between devices and the cloud. While they may be part of a broader platform, their core function is to provide reliable connectivity infrastructure. Examples include Cisco IoT Control Center and Ericsson IoT Accelerator.
Application enablement platforms (AEPs).These platforms provide the tools and services required to develop, deploy, and manage IoT applications. They often include development frameworks, SDKs, pre-built components, data visualization tools, and device integration and deployment support. While they may offer device and data management capabilities, their primary focus is application development. Well-known AEPs include AWS IoT, Microsoft Azure IoT, and Google Cloud IoT Core.
IoT analytics platforms. These platforms specialize in managing and analyzing the vast amounts of data generated by IoT devices. They support data ingestion, processing, modeling, and advanced analytics. Key features include real-time analytics, data visualization, machine learning, and predictive and prescriptive analytics. These platforms help identify patterns, trends, and correlations, providing actionable insights from IoT data. Examples include Splunk and Tableau.
IoT cloud platforms. Built on cloud infrastructure, these platforms support IoT solutions’ full development and management. They provide device management, data storage, processing, analytics, and application development services. Their cloud-based nature ensures scalability and flexibility, making them suitable for large-scale deployments. Examples are AWS IoT, Microsoft Azure IoT, and Google Cloud IoT Core.
Industrial IoT (IIoT) platforms. Tailored for industrial applications, these platforms offer features like asset management, predictive maintenance, operations management, and integration with industrial control systems. They emphasize enhanced security and reliability. Notable platforms include ThingWorx, Siemens MindSphere, and GE Predix.
Hardware-specific platforms. These platforms are designed for specific hardware environments. For example, Arduino IoT Cloud is built for Arduino and compatible boards, while Raspberry Pi OS supports its own IoT ecosystem. Features and capabilities vary depending on the hardware.

How IoT platforms operate

An IoT platform acts as a bridge between IoT devices and the cloud. It provides integrated services that enable the connection, integration, management, and data processing of connected devices.

The services and functions offered by an IoT platform can be divided into the following operational phases:

Device connectivity and management. This is the first phase of operation on an IoT platform. The platform provides mechanisms for securely registering and linking new IoT devices to the system. This may involve creating device IDs, generating authentication keys, and setting configuration options. The platform may use various communication protocols such as MQTT, CoAP, HTTP, Bluetooth, Zigbee, and LoRaWAN to establish communication with the device. It serves as a gateway that converts and transmits data from devices to the cloud. Once devices are connected and configured, the platform monitors their status and health remotely. It can also send commands and configuration updates to the devices.
Data ingestion and processing. Once connected, devices send data such as sensor readings, status updates, or requests to the platform. The platform receives this data through message brokers or APIs. The ingested data is then processed either in real time or in batches. Data processing may involve filtering, transforming, aggregating, and analyzing the data.
Data storage. The processed data is often stored in a platform-provided or integrated database, which may be a time-series, NoSQL, or relational database system. Stored data can be used for historical analysis, visualization, or triggering actions.’
Data analytics and visualization. Many platforms offer tools and services for analyzing stored data. These range from basic dashboards and visualizations to advanced machine learning and predictive analytics. The goal is to extract meaningful insights from device data.
Application enablement. The platform may provide APIs and SDKs that allow developers to build applications that interact with connected devices and processed data. These applications can be used for monitoring, control, automation, or user interaction.
Security. The platform may include features to secure device communication, authenticate devices, encrypt data in transit and at rest, and manage access control.

When is an IoT platform needed?

Not all IoT solutions require a dedicated platform. However, using a platform becomes increasingly important as an IoT system grows. In most real-world applications, an IoT platform is highly beneficial and often essential for building a reliable, scalable, and manageable solution.

Below are common scenarios where an IoT platform becomes necessary:

Multiple connected devices. Individual control becomes inefficient when your application involves more than a few connected devices. Managing configurations, updates, and monitoring grows more complex as the device count increases. Manual management may suffice for small-scale use, such as a few home sensors. But beyond 10 to 20 devices, platform-based management becomes crucial. An IoT platform is essential for centralized onboarding, organization, and lifecycle management for systems with hundreds or thousands of connected devices.
Significant data volumes. If your devices generate continuous data that must be collected, stored, and analyzed, an IoT platform provides the backend infrastructure needed. Even a small number of devices can produce significant data volumes if they transmit frequently. When your application requires real-time reactions, such as alerts based on sensor readings or immediate control responses, an IoT aplatform’s ingestion and processing capabilities are critical.
Need for remote management and control. A platform provides the necessary communication channels and management interfaces for remotely monitoring and controlling IoT devices.
Requirement for data analytics and insights. Platforms often include dashboards, reports, or advanced analytics tools, making it easy to generate insights from data using these tools or integrating with external analytics platforms.
Application development or integration. A platform provides essential APIs and integration tools for building user-facing applications or integrating IoT data with other enterprise systems.
Focus on business logic. Using an appropriate IoT platform is the most effective approach if your development team needs to focus on business logic rather than infrastructure concerns like device connectivity and data processing.
Long-term scalability. If you expect IoT deployment to grow over time, starting with a platform provides a scalable foundation that supports future expansion.

The top IoT platforms

There are many IoT platforms available, falling into different categories. However, cloud platforms are generally preferred due to their comprehensive packages for developing and managing IoT solutions.

Some of the top IoT platforms in 2025 include the following:

Amazon Web Services (AWS) IoT is a mature and widely adopted platform offering a broad range of services, from device connectivity and management to advanced analytics and machine learning integration. AWS supports a wide array of IoT use cases across industries.
Microsoft Azure IoT provides a comprehensive suite of IoT services and is known for strong integration with other Microsoft enterprise tools. It places particular emphasis on edge computing capabilities.
Google Cloud IoT is built on Google’s expertise in data analytics, AI, and machine learning, this platform is known for its scalability and powerful data processing features.
Software AG (Cumulocity IoT) currently leads in the industrial IoT (IIoT) space. It offers a flexible “buy and build” approach, with strong features in device management and application enablement.
PTC (ThingWorx) is tailored for industrial applications, ThingWorx provides stong support for digital twins, augmented reality, and industrial connectivity.
Particle is an end-to-end platform with hardware, connectivity, and cloud services. It is a popular choice for companies seeking an integrated solution, particularly for prototyping and scaling projects.
Siemens (Insights Hub) is a major player in the IIoT space, offering advanced analytics and AI integration for industrial data-driven insights.
IBM Watson IoT focuses on and excels at AI-powered IoT solutions, offering sophisticated analytical capabilities through integration with IBM’s broader AI and data services.
Oracle IoT is known for its strong analytics capabilities and is widely used in smart manufacturing and logistics industries.

A free tier

Most popular IoT platforms offer a free tier to allow developers to get started and experiment. The specifics of these tiers, such as limits, duration, and features, can vary.

Here are some details:

AWS IoT Core: The free tier lasts for the first 12 months after you create your AWS account. It includes 2,250,000 minutes of connection, 500,000 messages, 225,000 Registry or Device Shadow operations, 250,000 rules triggered, and 250,000 actions applied. The free tier for AWS IoT Analytics is also valid for the first 12 months. It includes 100 MB of data processed, 10 GB of processed data storage, 10 GB of raw data storage, and 10 GB of data scanned for query execution per month.
Microsoft Azure IoT Hub: The free tier includes connecting up to 500 devices and up to 8,000 messages per day. Each Azure subscription can have one free IoT hub. The free tier is intended for testing and evaluation.
Google Cloud IoT Platform: The free tier is part of the Google Cloud Free Program. It includes a $300 credit for new users and free monthly usage of certain products. This gives free access to components like Compute Engine, 5 GB Cloud Storage, and 10 GB of Pub/Sub messages per month.
Particle: It offers a free forever plan for up to 100 devices. This includes unlimited development devices and up to 100 cloud-connected devices with limited data operations.

Choosing an IoT platform

Several factors must be considered when selecting an IoT platform. First, you need to identify your specific requirements, such as your use case, the number and type of devices, the volume and velocity of data, needs for data visualization and analytics, security requirements, integration with enterprise systems, and scalability.

Next, evaluate different platforms based on several criteria: technical complexity, connectivity options, ease of use, universality, scalability and extensibility, flexibility, security, data storage, processing speed, cost, application enablement, visibility, and technical support.

Based on this evaluation, you can shortlist a few platforms that best meet your needs. Use free tiers or trial periods to test these platforms with your actual hardware and use case. Pay attention to the ease of setup, device integration, data flow, and the overall development experience.

Finally, after gaining hands-on experience through the free tier or trial, consider long-term factors such as the risk of vendor lock-in, platform maturity, available support, and the strength of the developer community.