Why investors bet on Dremio’s data analytics play

Big data vendors have done a terrific job selling enterprise decision makers on the value that data analysts and data scientists can deliver using their products. And while their marketing pitches might be spot on, their customers are often frustrated by the amount of time it takes to get the data-driven insights they are looking for.

No one is to blame. It takes time to move data from data lakes, to data warehouses, to data cubes so that BI and predictive tools can be applied. Not only that, but unless you’re a company like Facebook, Amazon, Alibaba or the like, IT doesn’t have the manpower to serve everyone at the same time.

Dremio solves the problem

If that sounds like a problem waiting to be solved, then you probably aren’t familiar with Dremio. The Mountain View, Calif-based self-service data analytics provider came out of stealth last July and introduced a product bearing the company’s name. With Dremio, data analysts and data scientists don’t have to wait for IT to set up the data infrastructure to access the information they need to do their work.

Dremio already claims customers (like Mercedes-maker Daimler and European cloud computing provider OVH) on its customer list which spans four continents and a wide range of industries like healthcare, manufacturing, automotive, high tech, and financial services. Best-in-class business intelligence (BI) and analytics providers like Microsoft, Qlik and Enigma Technologies are Dremio partners.

Investors bank on the solution

For a 7-month old company that might seem like enough good fortune, but there is also this- Dremio just announced a $25M Series B round of funding provided by new investor Norwest Venture Partners as well as existing investors Lightspeed Venture Partners and Redpoint Ventures.

Tomer Shiran, cofounder and CEO at Dremio, says that while he and his team weren’t actively looking for new capital, the opportunity to work with Northwest, as well as to deepen its relationships with Lightspeed and Redpoint came at a good time.

“It puts us in a great position to build out the product and our go to market team,” says Shiran, adding that over the next year he expects Dremio to approximately double in size, with most of the growth taking place in areas like engineering and customer success. Opening new offices outside of the company’s Mountain View headquarters is also in the plans.

Engineered for the speed of Google

Dremio (the product) is based on four areas of innovation, among them Apache Arrow’s execution engine, Dremio Reflections (physically optimized representations of source data), Native Push-downs (Optimized query semantics for each data source — relational, NoSQL, HDFS, Amazon S3…), and Universal Relational Algebra (cost-based query planner automatically substitutes plans to make optimal use of Dremio Reflections.)

Shiran says that the product is being continuously updated. “We’ve managed to ship a new release with new features almost every month since launch,” he says, noting that in these early stages of the product they are intent on moving quickly in order to “embrace the feedback of users and continue to make the product better and better.” One of Dremio’s advantages is that it is open source and has an active community that is continuously providing feedback.

“We have the benefit of hearing about the experiences of all these users and their diverse needs and their hugely different technology environments,” says Shiran,

Dremio’s team has also had their ear to the ground listening for customer pain points and wish lists as well as observing how Dremio is being used.

Attuned to customer feedback

“One of the things we learned is that many companies have central analytics environments that are multi-tenant in nature. What I mean is that different departments or teams within the company are each treated as a “customer” and share the analytics infrastructure. Just like any SaaS company with a multi-tenant offering, it is important to be able to make sure the needs of one tenant don’t drown out the needs of other tenants. So this is an area we have made big improvements in Dremio since launch, and will continue to make going forward,” he says.

Other improvements involve enhancements in the area of management to meet the needs of the company’s very large customers with mission critical systems with complex integrations and deployment requirements. “We’ve added several features to make it easier to deploy and manage Dremio for these users,” says Shiran.

What don’t people know about Dremio?

Like with any new product, many don’t yet know that Dremio, or even anything like it, exists, “or is even possible,” says Shiran. He uses an analogy to describe the current state that data analysts and data scientists are working in, “It reminds me of about 10 years ago before the iPhone, we were walking around with all these different devices — a phone, a camera, a GPS device, calculator, and so on — and we had no idea this could be a single thing that was smaller and easier to use than these traditional devices. That’s what Dremio is like.”