Sharpened edge needed for IoT edge databases

Sharpened edge needed for IoT edge databases

Sharpened edge needed for IoT edge databases

As more IoT data is processed out on the edge of networks, on or near devices, the awareness that edge databases need to get smarter has sharpened. Edge computing, in other words, is now the ‘cutting edge’ of the IoT, and it’s never been more important to understand the mechanics of edge databases and their advantages. 

 

A little (edge) knowledge is a dangerous thing

For IT organizations, it’s all well and good to understand that the IoT edge needs to be more intelligent – but a little edge computing knowledge can also be a dangerous thing.

Most conventional IoT architectures focus on two main end-points:

  1. The sensors, devices, network switches and other intelligent connection points, from RFID tags onwards.
  2. The cloud server in the data center, tasked with applying storage, analytics and wider aspects of deduplication, filtering and other forms of data management.

What the IoT needs is a less binary approach, a more scalable approach to architectural delineation. What the IoT needs is a more elastic middle tier, capable of sitting at the ‘edge’ of the network, but one that also provides a higher level of robust processing, data management and analysis services than is currently being postulated, or indeed developed, by many of the software developers working at this level.

Mike Hoskins, product and technology evangelist at data management company Actian, agrees with this view. He advises that the sheer volume and repetition of sensor data make it impractical for most organisations to imagine landing all sensor data in the cloud.

“[A new generation of] smarter IoT architectures will provide an intelligent middle tier – a kind of gateway function that resides near the sensors, at the edge. This layer is intended for early capture, processing and local analysis of the sensor data, before only vital information is sent to the cloud,” he writes in a recent blog post.

The edge advantage

Actian advocates that the most natural technology to deploy at the onboarding edge of the network is a bullet-proof, tougher and altogether smarter embedded IoT edge database.

So what do we get with this sharper edged edge IoT database? Hoskins says that immediate advantages included persistence and security.

“{But wider than these benefits], you could also apply crucial local filtering (e.g. duplicates, errors, steady states etc.) and data operations (e.g. sorts, aggregates, model application and local analytics) on the data, prior to it ‘landing’ the data in the cloud – a much more efficient and productive set-up for cloud-based analytics of sensor data,” he states.

Read more: Microsoft unveils Azure IoT Edge at Build 2017 conference

It’s a hybrid world, after all

As well as this approach to hybrid IoT edge databases, Hoskins and team also wax lyrical over the benefits of hybrid integration technologies and a more hybrid treatment for data processing.

Actian has put its weight behind a model called HTAP (Hybrid Transactional/Analytical Processing). It’s a Gartner-coined term that describes a hybrid, converged software infrastructure capable of handling both traditional transactional data management workloads as well as modern analytic data management workloads.

There are no prizes for guessing that Actian is, indeed, a hybrid architecture specialist. Okay, so it’s a loaded message from this company, maybe – but there’s enough technical justification and validation to warrant Actian airing this issue.

At least, we think so. IoT architecture, as of 2017, is hardly an open and shut case now, is it?

Read more: AWS launches Greengrass for IoT edge computing