When Mulling IoT Storage Options, Location Matters

The growing amount of data IoT sensors and machinery generate is forcing companies to rethink their IoT storage strategies.

“Right now, they don’t really know what data is actually useful, and, once analyzed, what business decisions can be helped by that information,” said Dilip Sarangan, global research director, IoT and digital transformation, at Frost & Sullivan. 

The 24 billion IoT devices that Gartner estimates will be in use by next year are producing “a ridiculous amount of data that’s just a whole lot of noise right now,” Sarangan said. The question, therefore, is whether to keep it and if so, where to store it.

The push for storage in the cloud, the prime destination for the past several years, is now turning back to on-premises and edge storage, analysts said. And the determination is made application by application — and location by location.

Many organizations with IoT don’t need to go to the cloud, Sarangan said. “They mostly want it on-prem and localized,” he said, especially with latency issues that won’t zero out even in the next decade. “Transmitting data to the cloud doesn’t make sense when most of the applications at the edge need at least a real-time aspect to analysis.”

Eric Burgener, research vice president, infrastructure systems, platforms and technologies, at IDC, agreed that the decision about where data analysis takes place will drive the purchase decision on storage capacity, whether data is stored in the core, or onsite datacenter, in the cloud, or increasingly, at the edge. 

Tiered IoT storage options in the cloud, from hot to cold, for example, are less relevant in IoT applications, given the possibility of storing data more locally, according to Burgener. With tiered storage, he said, the basic concept is all data doesn’t have to be stored in the same high-performance, high-cost storage area. 

“You only put data there that has to be delivered with high performance and opt for cheaper tiers for data that you don’t need on premises or need access to all that frequently,” he said.

Use cases in which data needs to be analyzed immediately, such as autonomous vehicles, rules out cloud storage. Less time-intensive use cases allow data to be sent back to a central location where machine learning is applied to garner insights. 

Certain industries and applications generate significant quantities of data including, utilities, building automation systems (lighting, heating), and surveillance systems. Those surveillance cameras, for example, transmit about 2 megabytes of data per second. 

The mix of IoT storage types is attuned to how enterprises want to use it, Burgener said. You might see hundreds of terabytes and tens of petabytes in storage in the data center, but less than a 20-terabyte storage device in an edge location, he said.

Edge devices don’t necessarily need processing power or a ton of storage, just the ability to capture data and send it back to a more centralized location for processing. And depending on where they’re located, those devices need to be ruggedized for weather and have enough power to maintain data until batteries can be changed.