Azure IoT vs AWS IoT vs Google IoT Pricing: Feature Comparison Chart for Enterprise [2025]

Introduction

The Internet of Things (IoT) helps businesses run better by connecting devices, collecting information, and improving choices. But picking the best IoT cloud provider can be confusing. The main three are AWS IoT vs Azure IoT vs Google IoT. Some businesses choose Azure IoT over AWS IoT because it works better with Microsoft tools. Others prefer Google Cloud IoT instead of AWS IoT because it’s great for data analysis.

Why Pricing and Features Matter for Businesses

Businesses need to think carefully before choosing an IoT platform. Here’s why:

• Scalability:

The platform should grow with the business without becoming too expensive.

• Security & Compliance:

Businesses must protect their data and follow security rules. IoT cloud providers should offer strong security features.

• Compatibility:

If a company already uses Microsoft tools, it might compare AWS IoT Core and Azure IoT Hub. Others may check Google IoT Platform and AWS IoT to see which fits better.

• Cost vs Value:

The cheapest option isn’t always the best. Some platforms offer extra tools that help businesses in the long run.

In this blog, we will provide an IoT Platforms Comparison: AWS IoT vs Azure IoT vs Google IoT Core, focusing on their pricing, features, and business benefits.

Key Features of AWS IoT, Azure IoT, and Google IoT

When choosing an IoT cloud service, businesses look for tools that help them manage devices, keep data safe, and analyze information. AWS IoT, Azure IoT, and Google IoT all offer these features, but they do things a little differently.

Managing IoT Devices

Companies with thousands of smart devices need an easy way to control them.

AWS IoT Core lets businesses connect and manage devices, but it can be tricky to set up, especially for companies that don’t already use AWS services.

Azure IoT Hub makes this process simpler, especially for businesses that use Microsoft products. It also includes Azure IoT Edge, which allows devices to process data locally instead of sending everything to the cloud. This is helpful when internet access is slow or unreliable.

Google Cloud IoT used to have a service called Google IoT Core, but it was discontinued. Now, businesses must use other Google tools to manage their devices, which can be more complicated.

Keeping IoT Data Safe

Security is one of the biggest concerns and challenges in IoT cloud services because connected devices can be hacked if they aren’t well protected.

AWS IoT Core has strong security features, including encryption (which protects data) and identity management (which controls who can access the system).

Azure IoT Hub takes security a step further by working with Microsoft Defender for IoT. This tool helps businesses detect threats and stop cyberattacks before they happen.

Google Cloud IoT also offers encryption and identity management, but businesses may need to set up these tools manually to get the most protection.

Using AI and Data Analytics

IoT devices gather a lot of data, but businesses need analytics tools to make sense of it.

AWS IoT Core works well with AWS SageMaker, which helps companies use AI to predict trends. However, setting up analytics on AWS can take extra effort.

Azure IoT Hub connects easily with Azure AI and Power BI, making it simple to track trends and create reports. This is especially useful for businesses already using Microsoft tools.

Google Cloud IoT is great for data analysis. It works with BigQuery and Vertex AI, which are some of the best tools for handling large amounts of data. But since Google IoT Core was discontinued, businesses might need extra setup to get everything working.

Let’s compare the pricing of these platforms to help businesses find the best value.

AWS IoT vs Azure IoT vs Google IoT – IoT Platform Pricing Comparison

The cost of using an IoT cloud platform is a key factor for businesses that want to connect and manage smart devices. However, pricing is not always straightforward. There are different types of costs, and if businesses don’t plan carefully, they might end up paying more than expected.

Here, we’ll explain how AWS IoT, Azure IoT, and Google Cloud IoT charge for their services in a simple way. We’ll also cover hidden costs that can add up over time.

1. How Do IoT Cloud Platforms Charge?

Before comparing the three platforms, let’s first understand how IoT pricing works. These services don’t have a single fixed cost; instead, they charge for different things based on how much and how often you use them.

Message Pricing (Cost of Sending and Receiving Data)

Smart devices send and receive data (known as messages) over the internet. The more messages a device sends to the cloud (or receives from the cloud), the more you pay.

All three platforms—AWS, Azure, and Google—charge per million messages. Some offer discounts if you send a very large number of messages, while others stick to a flat rate.

Device Management Fees (Cost of Keeping Devices Running Smoothly)

Managing connected devices involves things like software updates, tracking device health, and fixing issues remotely. While some basic features are free, advanced features—such as bulk updates and automatic monitoring—may come at an extra cost.

Storage Costs (Saving IoT Data for Future Use)

IoT devices gather a lot of data, and businesses often need to store this information for future use or compliance reasons. Some cloud platforms provide a small amount of free storage, but beyond that, they charge based on how much data is stored and how long it’s kept.

Security Costs (Protecting IoT Devices and Data)

While basic security features like encryption and password protection are included, advanced security options such as extra authentication, real-time threat detection, and compliance with industry standards often come at an additional cost.

Analytics & AI Costs (Processing and Understanding IoT Data)

Many businesses analyze IoT data usingAI and machine learning tools. Some cloud platforms include basic data analytics for free, but advanced AI-powered processing requires extra payment.

2. Free Tiers – Testing IoT Platforms Without Paying

Most cloud providers let businesses use their IoT services for free at first, so they can try them out before paying. However, each provider offers different free benefits.

• AWS IoT Core: Offers 500,000 free messages per month for the first 12 months only. After a year, standard charges apply.
• Azure IoT Hub: Provides 8,000 free messages per day (about 240,000 messages per month) without a time limit.
• Google Cloud IoT Core: Does not offer a specific free tier but gives a $300 free credit to use across all Google Cloud services, including IoT.

3. Paid Plans – Understanding Ongoing IoT Costs

After the free period, businesses have to pay based on their usage. Here’s a look at how the pricing compares:

• AWS IoT Core: Charges $1.00 per million messages. However, businesses must pay extra for security, device management, and data analytics.
• Azure IoT Hub: Starts at $0.80 per million messages, which is cheaper than AWS. Some basic security and device management features are included.
• Google Cloud IoT Core: Costs $0.45 per million operations, making it the cheapest per message. However, it doesn’t include built-in security or device management, so businesses must pay for separate services.

While Google IoT Core seems the cheapest per message, the total cost may increase due to separate security and management services that are included in Azure’s plan.

4. Hidden Costs – Extra Fees That Affect Total Expenses

Along with the standard pricing, businesses should also be aware of extra costs that can significantly impact on the final bill.

Data Transfer Fees (Moving Data Between Cloud Services)

When IoT data moves between different services, some platforms charge an extra fee:

• AWS IoT Core: Charges separately for transferring IoT data to other AWS services.
• Azure IoT Hub: Includes some free data transfers, but large amounts of data still incur costs.
• Google Cloud IoT Core: Also charges extra for moving data, depending on where it is stored and accessed.

Security & Compliance Fees (Extra Protection for IoT Systems)

While basic security is included, advanced security tools cost more:

• AWS IoT Device Defender: Extra cost for real-time threat detection and compliance monitoring.
• Azure IoT Hub: Includes some basic security but extra features require payment.
• Google Cloud IoT Core: Requires businesses to buy separate Google Cloud security services.

Edge Computing Fees (Processing IoT Data Closer to Devices)

Instead of sending all data to the cloud, some businesses use edge computing to process information closer to the device. Each cloud platform has different pricing: AWS Greengrass vs Azure IoT Edge vs Google Cloud IoT Core.

• AWS Greengrass: Paid add-on for edge computing.
• Azure IoT Edge: Included as part of Azure IoT Hub, making it cheaper for businesses using both cloud and edge computing.
• Google Cloud IoT Core: No built-in edge computing, requiring third-party tools, which adds to the cost.

Long-Term Storage Fees (Keeping IoT Data for Future Use)

Since Internet of things (IoT) devices generate huge amounts of data, long-term storage fees can quickly add up.

• AWS: Charges based on how much data is stored and for how long (using AWS S3 or AWS DynamoDB).
• Azure: IT includes some storage in IoT Hub plans, making it more cost-effective for businesses storing data long-term.
• Google Cloud: Requires separate storage plans, which can increase costs over time.

5. What Affects the Cost of IoT Services?

The total cost of using an IoT cloud platform depends on several things, such as:

• Number of Messages Sent: The more messages a business sends between devices and the cloud, the higher the cost becomes. Some platforms provide discounts and offers when sending large amounts of data.
• Device Management: Companies that need automatic software updates, remote monitoring, and troubleshooting need to pay extra for these services.
• Security Needs: Healthcare and Banking industries need extra security to safeguard their data. Adding these security features can make the service more expensive.
• Data Analysis and AI: Businesses that use real data tracking or smart technology may have to pay extra for these advanced features.

By understanding these costs, businesses can plan better and choose an option that fits in their budget.