SaaS vs PaaS vs IaaS: Finding the Best Fit for Your IoT Project

An IoT project without the cloud is like a car without fuel — it won’t go anywhere. To make it work, you need to choose the right cloud computing model — and that’s where it gets challenging.

You’ve likely faced tough questions: How do I keep costs manageable? How do I integrate connected devices with cloud systems smoothly? What’s the fastest, most reliable way to launch my IoT solution without drowning in technical complexity?

Choosing a cloud service model — whether Infrastructure as a Service (IaaS), Platform as a Service (PaaS), or Software as a Service (SaaS) — is a way to get answers to these lingering questions. Each model comes with its benefits, trade-offs, and use cases, and we’re about to explain them.

Having delivered expert IoT development services to over 100 clients, we know what it takes to pick a suitable cloud model for your IoT project. From providing SaaS platforms like Propuskator and 2Smart Cloud and PaaS solutions like 2Smart Standalone to setting up IaaS environments on GCP and AWS, we’ve done it all. So, let’s get a behind-the-scenes look at what works and why.

Highlights:

• IaaS — think AWS or GCP — is the way to go if you’re working on a large-scale, resource-heavy IoT project.
• Consider PaaS a sweet spot if you’re building custom apps for your IoT devices. Our 2Smart Standalone is a great example!
• Looking for something quick to set up? Think about SaaS solutions like 2Smart Cloud or Propuskator.

A 2Smart Standalone PaaS solution

Kostiantyn Oliynyk

Head of IoT at Webbylab

Helped dozens of startups create effective IOT products.

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Understanding the Cloud Service Models for IoT

As we’ve briefly mentioned, cloud models like IaaS, SaaS, and PaaS constitute the three main types of cloud computing. Let’s explore how each fits into the unique requirements of Internet of Things projects.

Infrastructure as a Service: Full Control for Advanced Customization

IaaS offers the building blocks for IoT projects — such as virtual machines, storage, and networking. With this model, you gain full control over the infrastructure and can configure it following your requirements.

Platform as a Service: Flexibility for Developers

PaaS provides a platform — hardware and software tools — for application development, testing, and deployment. In this cloud computing model, you manage the apps and data while the IoT PaaS providers take care of the infrastructure, operating system, and runtime environment.

Software as a Service: Simplified and Ready-Made Solutions

SaaS delivers the easiest use of cloud models, offering ready-to-use software applications. Within this model, you access and leverage apps while the service provider manages everything, from the infrastructure to the software itself.

Comparing IaaS, PaaS, and SaaS for IoT Projects [+ Real-Life Examples]

Now that you’ve learned the basics of the cloud service model, let’s take a closer look. Here are the IaaS, PaaS, and SaaS models along with their advantages, limitations, and real-world applications explained:

IaaS Cloud Solution: Pros, Cons, and Use Cases

With an IaaS operating model, you get the following perks:

• Complete control. You can control every aspect of the environment, configuring it for the specific IoT application’s needs.
• Flexibility. You can choose and configure the operating system, storage, and network resources following your project’s requirements.
• Scalability. You can increase or decrease resources as necessary — a solid benefit for IoT applications with variable workloads.

Nevertheless, you may also have to deal with the following limitations of IaaS:

• Higher complexity and management burden. IaaS requires more attention, which can be time-consuming and complicated.
• Potentially higher costs. Depending on the use, IaaS can be costly, especially if you don’t control scaling properly.

And, finally, how can IaaS be used in IoT? Here are the top use cases we highlight:

• Virtual machines for IoT data processing. You can configure virtual machines to collect, process, and store large amounts of data.
• Custom IoT gateways. You may require more specific connectivity options than Bluetooth or WiFi in IoT projects for gateways that support IaaS.
• Storage solutions. If your project generates huge amounts of data, IaaS lets you implement your own storage.

While we haven’t built IaaS solutions from the ground up, we use either AWS or GCP as infrastructure providers for our IoT projects. These IoT cloud platforms provide tools to securely connect, manage, and analyze data from IoT devices.

By the way! If you’d like to explore the IoT gateway topic further, don’t miss our latest post: What is IoT Gateways, where we discuss their role and applications in IoT ecosystems.

PaaS Cloud Solution: Pros, Cons, and Use Cases

Let’s move on to our next cloud model — PaaS. Here are its core advantages:

• Speed and efficiency. You (or your developers) can quickly build, test, and deploy applications without setting up the infrastructure.
• Integration with the IoT ecosystem. PaaS solutions often support integration with IoT protocols and data processing tools, making developing complex apps easier.
• Scalability. PaaS scales alongside your project as the number of devices and data streams increases.

The limitations to be aware of include the following:

• Less control over the environment. While PaaS offers more flexibility than SaaS, you still have limited control over some of the platform’s aspects.
• Provider lock-in risk. Moving your apps to another platform can be difficult because of dependency on APIs or specific PaaS components.

How can you use PaaS solutions? Here are a few ideas:

• Data processing platforms. You can leverage real-time data processing services to analyze large amounts of IoT data.
• Development and deployment environments. Platforms that support development and rapid deployment can seep up your IoT project by providing the necessary libraries, SDKs, and APIs.

For example, our 2Smart Standalone platform can be used as an automation solution for buildings of any scale. It provides monitoring tools, IoT protocol integration, and data analytics, among other things.

SaaS Cloud Solution: Pros, Cons, and Use Cases

Let’s now talk about the  undeniable SaaS benefits for IoT startups. Here are the most attractive ones:

• Rapid deployment. SaaS apps are typically ready to use and require minimal configuration.
• Less IT overhead. You don’t have to manage servers, storage, or application maintenance.
• Focus on core business. You can concentrate on the IoT solution itself without worrying about the backend.

Yet, consider these disadvantages before you choose cloud model:

• Limited customization. SaaS platforms may not be flexible enough for specialized IoT apps.
• Vendor lock-in. SaaS providers control updates and features, which can impact your project timelines or introduce unwanted changes.

The use cases of SaaS in IoT include:

• IoT data analytics. Many companies offer IoT SaaS software for collecting, visualizing, and analyzing data.
• Device management platforms. You can use SaaS solutions for device monitoring, diagnostics, and updates to manage devices at scale without developing these capabilities from scratch.

To better understand how SaaS works in real life, look at our Propuskator ACS. The solution is available both in the cloud and on-premises, offering tools for access control and management. Then, there’s our 2Smart Cloud platform, which can be used as a white-label solution for launching IoT devices to the market.

IaaS vs. PaaS vs. SaaS

Let’s recap all of the above and quickly go through our IoT cloud services comparison:

Choosing the Best Cloud Model for Your IoT Project

Choosing a cloud service model gets way easier when you know what to look into. Here’s a quick guide to help you make the right decision.

Step 1: Define Your Requirements

First off, identify the core priorities for your IoT project:

• Do control and management capabilities matter to you?
• How much flexibility and scalability do you need?
• Do you have any specific cloud security or compliance requirements?
• Is time-to-market important to you?

By going through the above questions, you’ll be able to set the core goals for control, scalability, flexibility, and security of your cloud-based solution.

Step 2: Consider Use Cases

The next step in selecting a cloud model for your IoT project involves determining the specific use cases you’re addressing. As we said, different models suit different scenarios:

• IaaS is perfect for custom-built solutions that require complete control.
• PaaS is ideal for IoT app development and real-time monitoring and analytics.
• SaaS is best for ready-to-use applications.

Step 3: Evaluate Your Resources

You likely want to choose cloud model that you can afford and manage easily. For that purpose, consider your:

• Technical expertise. Teams with profound IT skills can manage complex IaaS setups, while SaaS is ideal for non-technical users.
• Budget. IaaS can become expensive if not optimized, whereas SaaS and PaaS often offer cost-effective subscription plans.
• Timeline. If you’re dealing with tight deadlines, SaaS and PaaS allow for faster deployment.

Step 4: Leverage Our Self-Assessment PDF

To make your decision even easier, we’ve created a self-assessment document. Use it to choose the best cloud solution for IoT — whether IaaS, PaaS, or SaaS.

Picking the Right Deployment Model: An Ultimate Checklist

We’ve prepared a simple checklist if you still cannot decide on the most suitable cloud model for your IoT project. Go through the statements below and pick the right solution.

Choose SaaS if:

• You want a ready-to-use IoT platform with minimal setup. This is perfect for businesses that need quick deployment without worrying about infrastructure.
• Your main focus is on data analytics and device monitoring. Platforms like Azure IoT Central offer built-in dashboards and AI-driven insights.
• You’re looking to cut operational costs — the subscription-based model means you only pay for what you use, with no infrastructure maintenance.
• SaaS cloud examples — a smart home device manufacturer that needs an easy way to monitor IoT devices without building custom software.

Choose PaaS if:

• You need a flexible environment to build custom IoT applications. Solutions like AWS IoT Core allow developers to do this.
• You want more control over your app’s logic and integrations — PaaS IoT supports advanced event processing, cloud functions, and API integrations.
• You need scalability without dealing with infrastructure — the cloud provider handles hosting, networking, and databases so you can focus on your app.
• PaaS examples — an industrial IoT company developing a predictive maintenance system for smart factories, needing full control over device communication and application logic.

Choose IaaS if:

• You need full control over infrastructure and data processing — ideal for enterprises working with big data, AI, or high-performance computing in IoT.
• Security and compliance are top priorities — industries like finance, healthcare, or government benefit from custom security configurations.
• You plan to scale globally with custom infrastructure — IaaS solutions like Google Cloud Compute Engine or AWS EC2 offer complete control over networking and storage.
• IaaS cloud examples — a fleet management company processing millions of IoT sensor data points daily, requiring high-performance cloud computing.

Choose custom development if:

• You need a completely tailored IoT solution with no platform limitations — best for enterprises with unique business needs that off-the-shelf solutions can’t meet.
• Full ownership of data, security, and infrastructure is a must — a custom-built platform gives you total control over compliance, security, and integrations.
• Your project requires deep integration with legacy systems — common in industries like industrial automation, healthcare, and energy, where seamless integration is key.
• You’re prepared for a bigger upfront investment — custom development takes time and resources but offers long-term flexibility and cost efficiency.
• Custom development examples — an automotive company building a connected vehicle platform with real-time processing, edge computing, and proprietary security standards.

Real-World Use Cases of SaaS, PaaS and IaaS in IoT Projects

Before making your final decision on SaaS vs PaaS vs IaaS for enterprise IoT projects or startup initiatives, look at how these models are used in real life. Here are three tangible IoT and cloud computing examples:

1. Software as a Service: Device Analytics with Microsoft Azure IoT Central

Microsoft Azure IoT Central is a fully managed SaaS solution that works best for businesses looking to connect, monitor, and manage IoT devices at scale. Built-in analytics and customizable dashboards allow companies to gain insights quickly from their devices without worrying about infrastructure or custom development. It’s perfect for those needing a ready-to-go device monitoring and analytics solution.

2. Platform as a Service: Application Development with AWS IoT Core

AWS IoT Core offers a flexible PaaS environment where developers can build, deploy, and manage IoT applications. This platform supports secure device connectivity, message brokering, and integrations with other AWS services, like AWS Lambda and Amazon S3. Businesses that need more control over their application’s architecture can benefit from this service, as it allows for greater customization and scalability.

3. Infrastructure as a Service: Big Data Processing with Google Cloud

Google Cloud’s IaaS offerings — namely, Compute Engine and BigQuery — provide the infrastructure for processing and analyzing vast amounts of data from IoT devices. This is perfect for organizations with big data needs, as it offers scalable computing resources and storage. The platform’s capabilities also include advanced analytics, machine learning, and other data-intensive applications.

Start Your IoT Development with WebbyLab

WebbyLab has a solid background in different cloud computing models, including the ones we’ve discussed today. Here’s how we use cloud environments in our IoT projects:

Propuskator as a SaaS Solution

Propuskator, one of our IoT success stories, is nothing less than a perfect access control system for homes, offices, and enterprises of any size. The ACS can be deployed both via the cloud or on-premises.

A Propuskator mobile app

Key features include:

• A line of IoT based controllers developed to manage electric locks, gate drives, and barriers.
• Controllers can work both as part of the Propuskator ACS infrastructure or as autonomous devices controlled via a mobile app.

Our access control system can be used for:

• Remote control of gates, locks, wickets, and so on in a private house or facility, along with access administration — permanent or temporary.
• Employee access control and monitoring with detailed logs to track who entered and when.
• Access management for condominiums or developers to control entry to shared spaces.

2Smart Cloud as a SaaS Solution

2Smart Cloud is a white-label platform for vendors, which allows for the launch of new IoT devices or updating existing ones.

A 2Smart Cloud platform for device testing, deployment, and management

This platform supports established businesses, startups, or PoC/MVP development for IoT projects. It offers a public cloud version for testing and launching products, as well as on-premises solutions for businesses, complete with branding and custom mobile app capabilities.

Key features include:

• Tools for firmware development, testing, and versioning.
• App builder for creating custom web interfaces based on device data.
• Administration tools for managing connected devices, viewing historical data, and more.

On top of that, businesses get the opportunity to develop custom functionality upon request.

Some of the successful products we have already deployed based on 2Smart Cloud include the following:

• MyBox. A platform for EV charging and measuring devices with customized functionality for the charging station market.

A MyBox platform based on 2Smart Cloud

• Intellect. A solution for LED lamps, offering end users a mobile app for lamp control and monitoring.

A Intellect platform based on 2Smart Cloud

2Smart Standalone as a PaaS Solution

2Smart Standalone is an open-source smart home and automation system offering vendor-agnostic flexibility. It lets you manage devices from different manufacturers within one ecosystem, with the ability to create custom automation scripts.

A 2Smart Standalone platform for IoT ecosystem control and automation

The platform can be used as a:

• Facility monitoring system — whether it’s production sites, warehouses, greenhouses, and beyond.
• Smart home system for controlling devices within your network without cloud reliance.
• System for creating smart solutions, for example, a smart greenhouse.

A smart greenhouse based on 2Smart Standalone

The main advantage of 2Smart Standalone is its flexibility and the ability to integrate with any devices and communication protocols. It can also be used to develop your solution for your needs — not for commercial purposes.

Read also: IoT Use Cases in Agriculture.

AWS and GCP for IaaS Solutions

We use Amazon Web Services and Google Cloud Platform in many of our IoT projects. In particular, we used GCP infrastructure in our smart automated A/C drain line cleaner project. Both AWS and GCP offer tools to support the IaaS cloud service delivery model:

• AWS IoT Core. Connects millions of devices to the cloud, providing secure two-way communication. Supports MQTT, HTTPS, and LoRaWAN protocols for data transfer.
• AWS IoT Greengrass. Extends AWS IoT capabilities to edge devices.
• AWS IoT Analytics. Automates complex data analysis stages, allowing for filtering, transforming, and enriching IoT data.
• AWS IoT Device Management. Helps track, monitor, and manage your fleet of IoT devices.
• Google Cloud IoT Core. A fully managed service for connecting and managing devices. Supports MQTT and HTTP protocols.
• Google Cloud Pub/Sub. A messaging service that provides reliable and scalable data transfer between applications and devices.
• Google Cloud Dataflow. A streaming and batch data processing service for real-time IoT data analysis.
• Google BigQuery. A big data analytics service that allows you to quickly execute SQL queries on large data sets collected from IoT devices.

All in all, both platforms provide a scalable and reliable infrastructure for IoT projects. They let developers focus on creating innovative solutions without dealing with the physical infrastructure.

Conclusion

Cloud models like IaaS, SaaS, and PaaS have their own benefits and challenges for IoT projects. Choosing the right one depends on your project’s complexity, customization needs, budget, and team’s technical expertise.

So, before you decide on the cloud model for your IoT project, solidify your understanding by looking at the main differences:

As you can see, SaaS offers easy use of cloud models and rapid implementation, PaaS provides a flexible development platform, and IaaS — complete control over the infrastructure for customized cloud operations.

In case you’re still unsure which option is best for you, contact WebbyLab for a consultation. Having built SaaS and PaaS solutions firsthand and collaborated with popular IaaS vendors, we’re fully equipped to guide you.