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Actian today made available an update to an embedded database that promises to increase SQL query performance within mobile and edge computing applications by as much as 90% in certain use cases.
Based on a Btrieve transactional database architecture that employs the indexed sequential access method (ISAM) to store and retrieve data, the Zen V15 embedded database can be encapsulated in a set of Docker containers to make it easier to deploy.
Other capabilities added to the platform include time-series functionality to enable automatic collection, auditing, and delivery of data in near real time alongside existing support for transactions and document-centric applications.
Processing data at the edge
Btrieve databases have been in use since the early days of the PC. However, with the rise of mobile and edge computing applications, there is a resurgence in interest in the venerable database platform, said Lewis Carr, senior director of product marketing at Actian. Stateful applications that process data on edge computing platforms close to the point where it is created and consumed require local access to high-performance databases to minimize application latency, he noted. “Speed can really make a difference,” he said.
For example, an unsupervised inference engine created using machine learning algorithms will require access to a database to automate a process in real time, Carr added. That data generated by that inference engine can be secured using AES 256-bit encryption, he said.
Many of the databases employed in mobile computing applications are finding their way onto a wide variety of edge computing platforms that are running stateful applications. In many cases, it’s simply not practical to access databases over a wide area network (WAN) to drive those applications, many of which are core to the internet of things (IoT) platforms being incorporated into various digital business transformation initiatives.
Integrating tech and teams
Naturally, there is no shortage of options for deploying a database on an edge computing platform, which can span everything from an embedded system based on a Raspberry Pi board to a hyperconverged infrastructure (HCI) platform. In many cases, organizations will find themselves managing a slew of databases based on the preferences of individual developers. In other cases, a centralized IT team has set a database standard that needs to be maintained across a range of edge computing platforms.
Regardless of the approach, the amount of data being generated by edge computing platforms continues to increase. Rather than transfer all that data over a WAN to be processed and analyzed, organizations are adjusting to the fact that much of this raw data needs to be processed and analyzed at the edge. The aggregated results of that processing can then be shared more efficiently shared over limited WAN bandwidth.
It will be up to each organization to determine how best to achieve that. Many edge computing platforms are managed by operations technology (OT) teams that don’t report into a centralized IT organization. IT and OT teams typically have dissimilar cultures, and organizations frequently underestimate the amount of time and effort required to bring disparate teams together. Edge computing is playing a more strategic role with IT environments, which means integrating multiple technology fiefdoms is necessary to advance the goals of the business. As with most things involving culture within an organization, however, that is easier said than done.
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