Home Blog IoT Development Arduino vs Raspberry Pi: Key Differences & Comparison Table

Arduino vs Raspberry Pi: Key Differences & Comparison Table

April 6, 2023
11 minutes to read

Written by:

Kostiantyn Oliynyk

Kostiantyn Oliynyk

Head of IoT at Webbylab

Kostiantyn started his career in IT at Webbylab, where he quickly grew from the position of a tester to the role of a manager and business analyst. When the company’s management decided to develop the IoT direction, Kostia became one of its key figures.

FAQ
Can Raspberry Pi replace Arduino?

It depends on your specific project requirements and limitations. Arduino is a tiny, easy-to-use microcontroller that works well for small-scale projects that involve controlling physical devices and sensors. Raspberry Pi, compared to Arduino, is a small computer with more processing capacity and memory. It can replace Arduino if necessary, offering wider options for more complex tasks.

Can Raspberry Pi run Windows?

Yes, Raspberry Pi can run Windows 10 IoT Core, a version of Windows 10 for embedded devices and the Internet of Things apps. Yet, this isn’t a full Windows version. In this case, you can’t use a graphical user interface (GUI).

Can Arduino do everything Raspberry Pi can?

No, Arduino cannot do everything that Raspberry Pi can. Unlike Arduino, the latter offers more processing power, memory capabilities, a full-fledged operating system, more input/output options (e.g., HDMI, Ethernet), and audio, image, and video data processing features.

Why is Arduino not used in industry?

An Arduino board has some industrial applications but isn’t as widespread as Raspberry Pi. There are a few reasons, including limited memory and processing power, safety concerns, lack of industrial communication protocols, and scaling difficulties.

Do professional engineers use Arduino or Raspberry Pi?

Professional engineers may use both boards depending on the particular project. Arduino works well for home automation, robotics, and control systems. Raspberry Pi, on the other hand, is best for larger projects that need better processing capacity, like data analysis, AI, computer vision, etc.

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