AWS IoT and TagoIO solve the same underlying problem, getting data from devices into applications people can use, but they sit at different layers of the stack. AWS IoT is a set of cloud building blocks you compose into a solution. TagoIO is a full-stack IoT platform where the application layer is already built. Understanding that difference is most of the decision.
AWS IoT is Amazon’s family of managed services for device connectivity, anchored by AWS IoT Core (an MQTT broker with device registry, Device Shadows, and a rules engine that routes messages to other AWS services), alongside AWS IoT Greengrass for edge computing, AWS IoT SiteWise for industrial data, and AWS IoT Device Management for fleets. It runs at enormous scale and integrates deeply with the rest of AWS.
TagoIO is a full-stack IoT platform: device connectors, time-series storage, dashboards, a serverless Analysis engine for custom code in Node.js, Deno, or Python, Actions for rules and notifications, and TagoRUN for white-label end-user portals. It runs on AWS infrastructure itself, with dedicated deployments available through TagoDeploy in 12+ AWS regions. TagoIO also maintains a native integration with AWS IoT Core, so the two are used together in many production solutions.
TagoIO vs. AWS IoT comparison matrix
| TagoIO | AWS IoT | |
|---|---|---|
| Type | Full-stack IoT application platform | Cloud infrastructure services (PaaS building blocks) |
| Device connectivity | MQTT, HTTPS, 500+ pre-built device connectors, LoRaWAN via network server integrations (TTN, Actility, Loriot, ChirpStack, and others) | MQTT, MQTT over WebSockets, HTTPS, AWS IoT Core for LoRaWAN, Amazon Sidewalk |
| Dashboards | Built in, drag-and-drop, Blueprint dashboards for fleets | Not built in; typically Amazon Managed Grafana, QuickSight, or a custom app (SiteWise Monitor for industrial assets) |
| Custom logic | Analysis engine: serverless scripts in Node.js, Deno, or Python, triggered by data, schedules, or dashboards | Rules engine routing to Lambda, Kinesis, Timestream, S3, and other AWS services |
| End-user applications | TagoRUN white-label portal with user management, custom domain, and mobile app option | Build your own (Cognito, Amplify, custom web/mobile development) |
| Multi-tenancy for your customers | Built in via TagoRUN user management and Access policies | Design and build your own tenancy model |
| Edge | TagoCore, free and open-source edge engine | AWS IoT Greengrass, SiteWise Edge |
| Deployment | Multi-tenant cloud (US and EU) or dedicated instances via TagoDeploy in 12+ regions | AWS regions worldwide, fully managed |
| Pricing model | Free tier, then plan tiers (Starter $49/mo, Scale $199/mo) plus service usage; TagoDeploy from $850/mo | Pure usage-based: per connection-minute, per message, per rules action, per shadow operation |
| Security and compliance | ISO 27001 certified, GDPR compliant, TLS 1.2+ in transit, AES-256 at rest | Extensive AWS compliance portfolio, X.509 device certificates, IAM |
Architecture and what you build yourself
AWS IoT gives you primitives. IoT Core terminates MQTT connections, authenticates devices with X.509 certificates, and routes messages onward. What happens next is up to you: storage in Timestream or S3, processing in Lambda, visualization in Grafana or QuickSight, and an end-user application built by your team. That freedom is the point. Teams with cloud engineers get exactly the architecture they want, at whatever scale they need.
It also means a working proof of concept involves several services wired together, and a customer-facing product involves many more. AWS has been consolidating this layer: AWS IoT Analytics reached end of support in December 2025, AWS IoT Events follows in May 2026, and the Fleet Hub console retired in October 2025, with AWS pointing customers to general-purpose data services instead.
TagoIO packages that application layer. A device connects through a connector or the API, data lands in time-series buckets with configurable retention up to 9 years, dashboards read it directly, and Analysis scripts handle whatever custom processing the solution needs. The pieces are integrated because they were designed together.
Dashboards and end-user applications
This is the largest practical difference. AWS IoT has no general-purpose dashboard; SiteWise Monitor covers industrial asset portals, and everything else means pairing AWS data services with Grafana, QuickSight, or a custom frontend. If your deliverable is an application your customers log into, plan for frontend development, user management, and tenancy design on top of the AWS services.
In TagoIO, dashboards are part of the platform, and TagoRUN turns a project into a branded portal: your domain, your logo, your email templates, user signup, access policies, and an optional mobile app published under your name. For system integrators and OEMs whose deliverable is a finished application, this replaces a development workstream.
Custom logic and analytics
The AWS rules engine routes and transforms messages into more than 20 AWS services, which puts the full AWS data and ML stack at your disposal. Complex event logic lives in code you deploy and operate, usually Lambda.
TagoIO’s Analysis engine runs your scripts inside the platform, serverless, in Node.js, Deno, or Python, triggered by incoming data, schedules, or a button on a dashboard. Analytics reaches past dashboards as well, turning telemetry into forecasts and predictions inside the platform. For heavier pipelines, TagoIO data can flow out to external services, including AWS ones, through Actions and the API.
Pricing model
AWS IoT is metered per component: connection minutes, messages in 5 KB increments, shadow operations, rules actions, each billed separately, plus whatever downstream services the solution uses. Costs start near zero and track usage precisely, which rewards careful architecture and requires cost modeling at volume.
TagoIO combines plan tiers with service-based usage: data input and output transactions, storage, Analysis minutes, notifications, and end users. The free tier covers 5 devices, Starter begins at $49/month, Scale at $199/month, and TagoDeploy dedicated instances start at $850/month post-paid. A cost calculator on tago.io estimates monthly cost from expected usage.
The bottom line
AWS IoT makes sense when you have cloud engineering capacity, need deep integration with AWS data and ML services, or are building a bespoke product at very large scale where infrastructure-level control pays off.
TagoIO fits when the goal is a working IoT application, dashboards, alerts, custom logic, and a portal your customers use, without assembling and operating a dozen services. Many teams combine them, using the TagoIO integration with AWS IoT Core to keep AWS connectivity while getting the application layer from TagoIO.