If you are building an IoT solution for fleet management, EV telematics, or factory monitoring in India, your cloud platform choice comes down to two serious contenders: AWS IoT Core and Azure IoT Hub. Both are production-grade, both handle millions of devices, and both have data centres in India (Mumbai for AWS, Pune/Chennai for Azure). So which one should you pick?
Device Connectivity & MQTT
Both platforms support MQTT 3.1.1 for device-to-cloud communication, which is the standard protocol for IoT telematics. AWS IoT Core supports MQTT, HTTPS, and MQTT over WebSockets. Azure IoT Hub supports MQTT, AMQP, and HTTPS.
For fleet telematics where devices send small payloads frequently (GPS coordinates every 10 seconds, CAN data every second), MQTT is the right choice on either platform. Both handle it well.
Device Management
AWS IoT Core uses "Thing Shadows" (now called Device Shadows) to maintain a virtual representation of each device. You can query the shadow to see the last reported state even when the device is offline.
Azure IoT Hub uses "Device Twins" for the same purpose. Device Twins are slightly more feature-rich out of the box, supporting desired vs. reported property states and tag-based queries across your entire fleet.
For fleet operations where you need to query all devices with SoC below 20% or all machines with temperature above threshold, Azure Device Twins offer more powerful query capabilities natively.
Edge Computing
AWS offers Greengrass for edge computing. It runs on Linux devices and lets you deploy Lambda functions, ML models, and data processing logic to edge gateways. Greengrass can buffer data locally when connectivity drops and sync when it comes back.
Azure offers IoT Edge, which runs Docker containers on edge devices. This is more flexible than Greengrass for running complex workloads at the edge (e.g., a full Node-RED flow or a custom analytics engine).
For factory environments with unreliable internet, Azure IoT Edge with Docker containers tends to be more flexible. For fleet environments where edge hardware is constrained (small telematics box in a vehicle), Greengrass is lighter weight.
Analytics & Dashboards
AWS does not include a built-in dashboard. You need to add Amazon Timestream or Amazon Managed Grafana for visualization, and AWS IoT Analytics or Kinesis for stream processing. This gives you more flexibility but requires more setup.
Azure includes Time Series Insights (now Fabric Real-Time Intelligence) which provides out-of-the-box visualization for IoT time-series data. For teams that want faster time-to-dashboard, Azure has an edge here.
Pricing Model
AWS IoT Core charges per million messages. Azure IoT Hub charges per device per day (tiered by message volume). For high-frequency data (like 10-second GPS updates from 1,000 vehicles), the cost structure can differ significantly. AWS is cheaper for low-frequency, high-device-count deployments. Azure can be cheaper for high-frequency, smaller fleets.
The specifics depend on your exact workload. We model this for every client before recommending a platform.
Our Recommendation
If your team already uses AWS for other workloads, stick with AWS IoT Core. The integration with S3, Lambda, SageMaker, and the broader AWS ecosystem is seamless.
If your team uses Azure or Microsoft 365, Azure IoT Hub makes more sense. The integration with Power BI, Azure Digital Twins, and Dynamics 365 is compelling for enterprises.
If you have no preference, we typically recommend AWS IoT Core for fleet and EV telematics (simpler, cheaper for message-heavy workloads) and Azure IoT Hub for manufacturing (better edge computing with Docker, stronger device twin queries).
How Akran IQ Handles This
We are cloud-agnostic. We deploy on both AWS and Azure depending on what makes sense for each client. We set up the entire pipeline: MQTT broker, device registry, data processing, storage, dashboards, and alerts. You do not need to become an expert in either platform. That is our job.