Wasabi execs: 'We're growing at twice the speed of the market'

Cloud storage vendor Wasabi saw major expansion in 2023, fuelled by strategic European partnerships and emerging use cases

Cloud storage scale-up Wasabi Technologies claims it grew at double the market growth rate in 2023, thanks to an expansion in its channel partner network.

With major partners deals in Europe, such as Cancom in Germany, and new platform capabilities aimed at partners, the company now looks to emerging use cases in AI, security, and sustainability as additional tailwinds.

Speaking to CRN, EMEA VP and GM at Wasabi, Jon Howes and global VP of cloud strategy, David Boland, also outline the value proposition of simplicity, transparency, and efficiency.

Howes, for example, says the main industry challenge Wasabi is facing is the "guilt by association" due to the hyperscalers like AWS and Microsoft being under scrutiny in Europe for lock-in and egress fees.

"This doesn't directly impact us but highlights our value proposition. We offer zero egress fees, so customers can easily switch providers," he says.

"We articulate our differences around lock-in and transparency. It's an education process," adds Boland, explaining that Wasabi is investing time and effort into educating partners around how their method differs from hyperscalers.

Conquering Europe

Howes claims Wasabi has had a really strong year business-wise, particularly in the EMEA.

"We grew at about twice the market rate in cloud object storage. In the UK, we targeted partnerships selectively for coverage and vertical expertise.

"So we have broad partners like Softcat, and specialised ones like Coolspirit and Phoenix in areas like public sector and Academia.

"But we still prioritise quality over quantity."

He argues partners appreciate Wasabi for simplicity - its partner programme, in fact, is a one-price tier, with no hidden fees.

"And we save enterprises 80 per cent typically over hyperscalers."

Boland adds: "Our channel growth in Europe has been fantastic. We launched new platform capabilities like account management and white-labelling to help partners manage customers and rebrand our service as their own. This sets us apart from other providers."

He also explains how the company started initially trying to target channel partners, but was forced to go direct for a little bit.

"North America was initially direct sales from 2017-2019 until we had enough customers and demand for a channel approach.

"But in Europe and Asia, we have always been channel-focused given that experience."

AI, security and sustainability

Howes looks ahead at some interesting trends coming out of use cases - for example, security cameras requiring cloud storage.

"We are seeing potential in is security cameras and surveillance. Traditionally cameras stored footage on-premise, but we're starting to see projects adopt cloud storage instead. The economics are just as compelling for CCTV systems as for enterprise backup.

"So we view surveillance as an early stage use case for Wasabi with meaningful room for growth," he says.

And Boland adds: "With more security and perimeter devices being deployed, storing the increased data they generate can be complex and costly on-premise.

"That drives interest in offloading storage to the cloud. There is growing demand for cloud storage solutions among security teams as they roll out new camera systems and sensors."

And of course, Boland also discusses how Wasabi's cloud storage solutions fit into the AI pipeline.

He explains there are different stages of AI data usage:

• Ingesting raw data before transformation, ideal for cloud storage

• Processing and training data on performance-optimized infrastructure

• Checkpointing training data snapshots for recovery with cloud object storage

• Archiving trained models and outputs for compliance, also suited to object storage

But as models progress from v1 to v2, prior versions still need archiving.

So, object storage fits ingestion and archival phases, while specialised storage/compute handles the intensive middle training phase.

"The AI use cases have different needs - predictive analytics, generative AI, automotive, drones, etc.

"As AI adoption grows, companies must pick appropriate storage for each stage. We are well positioned given our low cost and no hidden egress fees, allowing efficient data lifecycle management," Boland explains.

Finally, he highlights that going into 2024, one of the main challenges company will have to reckon with is justifying increased compute and energy demands from advanced AI, while still achieving sustainability goals.