The short answer
For most connected products, AWS IoT and Azure IoT will both work — the deciding factors are your team's existing experience, who your customers are, and how you plan to process the data, not a feature checklist. Pick AWS IoT when you want a large menu of modular services to assemble yourself and expect heavy data processing or analytics. Pick Azure IoT when your customers are enterprises already standardized on Microsoft tooling, or when you want more of the device-fleet plumbing packaged for you out of the box. Either way, the architectural decision that matters more than the logo is keeping your firmware and business logic portable.
What an IoT cloud platform actually does for you
Before comparing, it helps to be precise about the job. An IoT platform supplies the building blocks every connected product needs:
- Secure per-device identity — a unique certificate or key per unit, provisioned in manufacturing, revocable if a unit is compromised.
- Message ingestion — millions of small telemetry messages arriving continuously, without you running servers.
- Command and control — sending instructions back down to a specific device, including devices that are asleep or offline.
- Device state — a cloud-side mirror of each unit's configuration, so the app can show state even when the hardware is unreachable.
- Fleet management and update delivery — the infrastructure behind OTA firmware updates, grouped rollouts, and version reporting.
- Storage, rules, and downstream processing — routing data into databases, dashboards, alerts, and analytics.
Building all of that yourself is a project in its own right, and it never stops needing maintenance. Both platforms sell it on consumption pricing, which is why a product with fifty field units and a product with a million units can sit on the same stack.
Where the two platforms genuinely differ
Philosophy
Amazon's platform is a toolbox: many small, composable services that you wire together. That gives you enormous flexibility and a huge library of adjacent services for data processing and machine learning, at the cost of more architectural decisions up front. Microsoft's platform leans toward a more integrated experience, with device provisioning, fleet configuration, and packaged solution templates that get a pilot running quickly.
Ecosystem gravity
This is the underrated criterion. If your product will be sold to hospitals, utilities, or industrial buyers whose IT departments live inside Microsoft identity and reporting tools, Azure removes procurement friction — their security review is shorter because it is familiar territory. If your product is consumer-facing or data-heavy, and your analytics roadmap points at large-scale processing, the AWS ecosystem is deeper.
Device-side effort
Both publish SDKs for common microcontrollers and both speak standard protocols, so the firmware effort is broadly similar. Your choice of silicon matters more here than your choice of cloud — see how to choose a microcontroller and, if you are weighing transport, MQTT vs HTTP for connected products.
Cost structure
Both start in the negligible range for a pilot fleet — tens of dollars a month is realistic while you have a handful of prototypes reporting. The structures differ, though, and the honest way to compare them is to model your own scenario: number of devices, message size, messages per device per day, retained storage duration, and how much downstream processing you will run. A chatty device that publishes every second costs radically more than the same device batching once a minute. Message design is a cost decision, not just an engineering one. Cloud cost is one line in the broader budget covered in IoT product development cost.
Criteria that should actually decide it
- Your team's existing skill. A team fluent in one platform will ship faster and make fewer security mistakes there. This outweighs most feature comparisons.
- Your buyer's environment. Enterprise buyers care where their data lives and which compliance certifications the platform holds.
- Data gravity. If the value of your product is analytics on the telemetry, choose the ecosystem where that processing will live.
- Regional and regulatory needs. Both offer broad regional coverage and strong compliance portfolios, but if you have data-residency obligations, verify the specific regions and attestations you need.
- Exit cost. How hard would it be to leave in three years? Answer this before you start, not after.
How to avoid painting yourself into a corner
The practical guidance we give clients is to treat the cloud as an interchangeable layer:
- Speak standard protocols on the wire so the device is not welded to one vendor's proprietary path.
- Keep a thin abstraction between your device-communication layer and your business logic, so swapping the transport does not mean rewriting the application.
- Document the message schema as a contract, versioned independently of both firmware and app. This also makes multi-version fleets survivable, which matters the moment you start staged rollouts.
- Keep raw telemetry exportable. Being able to walk away with your own history is what makes a migration merely annoying instead of impossible.
Firmware architecture choices interact with this directly — the update mechanism, the messaging layer, and the bootloader are all touched. See firmware development cost for how that scope is usually estimated, and BLE app development cost if a phone sits between the device and the cloud.
A reasonable default
If you have no existing preference and no enterprise buyer pulling you one way, start with whichever platform your engineering partner has shipped production fleets on, keep the device side protocol-standard, and revisit the decision at the point where your data volume becomes a real cost line. The wrong move is spending a month in comparison spreadsheets while the hardware sits waiting — both platforms are mature enough that the architecture you build on top of them is what determines success.
Talk it through before you commit
Projects House builds connected products end to end — electronics, firmware, cloud architecture, and app — so the platform decision is made once, with the whole system in view. If you are weighing cloud options for a device that does not exist yet, or inheriting a fleet that needs a better foundation, send us the details through our contact form and we will tell you what we would do and why. You can also browse our broader software development articles for related background.