Edge Computing Products – A Comparison

Edge Computing Products – A Comparison: Edge computing has been making waves over the last few years. IOT edge computing is bringing the data computation closer to the source of data generation. In an Edge IOT architecture, the edge gateways form the kernel of the system to create the IOT network. It is geographically located closer to the sensors.

Before edge computing, all of the data from the sensors were driven to the cloud. In IOT, the cloud became the center. It acted as a database to hold all the data from sensors from everywhere in the IOT network. It also hosted machine learning and Artificial intelligence. The importance of Iot is not just about collecting data. It’s about predicting what’s going to happen based on the past data and to detect anomalies and trends and drive action based on the data distribution.

The idea of edge computing is to accelerate the data processing, so if there is an anomaly, it is detected earlier, and real-time actions are drive. This way of processing means there needs to be hardware that is capable of storing data from the sensor, process it, and drive engagement and, if needed, send the data to the cloud. That’s where the significance of edge gateway comes in. There is a hub between the sensors and the cloud. Over the years, the role of gateway’s has grown from a simple device to hold data to a more robust system that can run AI and machine learning applications. 

Understanding IOT Edge Gateways

Typical IOT gateway is like a mini server. It should have the capability to manage the data that’s coming in from the sensors. It needs to store the data, so it needs to host a database. Since it connects downstream to the sensors, it should be capable of supporting the various network protocols used by a sensor, like Zigbee, 6LoWPAN, EnOcean, and others. Edge gateway should have the capability to manage the downstream and upstream the data. It will have to send the data upstream to the cloud. As edge computing is evolving the data analytics, machine learning is expected to be done at the edge. So edge gateways should be capable of supporting lightweight ML and AL. It should also have security built-in. Edge gateway should support data management that includes device identification, device connectivity, device provisioning, data storage, data analysis, and ML and AI. On the upstream, it has a connection to the cloud, manages the upstream data, and others. The gateway also isolates the device from the internet.

The IOT Gateway architecture will include the Gateway hardware, operating system, software stacks to support IOT connectivity protocols (MQTT and such)

Device management, sensor network protocol support, security stack, cloud connectivity.  

There are different gateway hardware explicitly released to address the need for edge computing. The hardware system should have a microprocessor, sufficient memory, capability to support the power operating system, support for cellular connection, Wifi/BT, wireless like BLE, 6LoWPAN, LoRA, Zigbee, Zwave and storage.

Edge Computing Products – A Comparison. We look at some of the available IOT Edge Gateway solutions in the market.

HPE Edgeline GL20

This hardware Gateway is capable of data acquisition, data analysis, and drive real-time action on the IOT devices. Its rugged performance and ideally suited for the harsh edge environment suitable for an industrial environment. 


  • Processor: Intel 4300U, two cores, 2.9Ghz
  • RAM: DDR3 8GB
  • Storage 64 GB SDD
  • Communication 3G, ethernet, 802.11bgnWiFi

OS: Linux Ubuntu Snappy, Wind River Helix, Windows 10 IOT Core

Dell Edge Gateway

Dell has Edge gateway 3000 and 5000 series that are built for the Industrial IOT solutions. These support the Intel E3805 series CPU and can support Ubuntu Core and Windows 10 IOT.


  • Processor: Intel E3805
  • RAM: DDR3 2GB
  • Storage 8 GB SSD
  • Communication 4G LTE ,3G, ethernet, 802.11bgnWiFi
  • OS: Linux Ubuntu Snappy, Wind River, Windows 10 IOT Core

Huawei AR series IOT Gateway

This gateway is also suitable for the industrial scenarios, rugged and dustproof, including anti-vibration and anti-electromagnetic radiation features, and has robust security features.


  • Processor: Dual Core 533Mh
  • RAM: DDR3 2GB
  • Storage 4GB flash
  • Communication 4G LTE ,3G, GPS, ethernet, 802.11bgnWiFi


Advantec offers RISC based WPAN network controller for IOT gateway. It is powered by Freescale i.MX6 Dual cortex A9 processor suitable for M2M and IOT application.


  • Processor: ARM® Cortex A9 i.MX6 Dual-core
  • RAM: DDR3 1GB
  • Storage 4GB flash
  • Communication ethernet, 802.11bgnWiFi

Mobodexter’s SMARTEDGE

SMARTEDGE offers a great Edge Computing configuration option including an Intel Xeon 32 Core processor with Antsle Private cloud operating system. Pre-configured Edge Analytics; Machine Learning and Artificial Intelligence software provides the best out-of-box experience for sensor data intelligence configuration.

  • Processor: Intel CPU @ 2.40 GHz, 8 Cores (Avoton C2750); & Intel Xeon CPU, 32 Cores
  • RAM: 16 GB ECC RAM
  • Storage: 2 x 500 GB SSD
  • antsleOS™ & antman™;
  • Communication ethernet, 802.11bgnWiFi

Edge Computing Products – A Comparison: Many players are coming up with many other configurations to help clients realize the potential of Edge Computing. Clients are seeing a wide range of options to choose from. This includes simple connectivity configurations to configuration with complex data mining capabilities.


  • Mobodexter, Inc., based in Redmond- WA, builds Internet of things solutions for enterprise applications with Highly scalable Kubernetes Clusters on the Edge. 
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