Fresh on the heels of our rebranding of the company from MapD last week, today we are excited to announce our Series C funding of $55M.
The round was led by Tiger Global Management, a global investment firm with $26 billion under management. When I first met Lee Fixel, the partner who leads Tiger’s private market investments, and his colleague Vince Hankes, I was struck by not only how much they already knew about our business, but their broad knowledge of the GPU software ecosystem and the big data analytics market. It was clear that they held a strong thesis around the massive market opportunity in front of our company, and were fully aligned with our vision of the disruptive power of GPU-accelerated analytics. We are delighted to welcome Tiger as shareholders of OmniSci, alongside participation from existing investors including In-Q-Tel, New Enterprise Associates, NVIDIA, Vanedge Capital, and Verizon Ventures. I would like to extend my deepest gratitude to all of our investors for their continuing belief in our vision and our team.
Our recent rebrand signified an important step in our journey. When we announced this we focused our communications on our vision. In this blog post I want to focus more on our mission statement and core values, and how they relate to this fundraising.
Our mission is to make analytics instant, powerful, and effortless for everyone. This is a somewhat deceptively simple statement. To live up to this requires us to do incredibly hard things:
First, as data continues to grow at 40% year over year, with little deceleration in sight, we need to continually raise the performance bar over time. With this exponential data growth, it gets increasingly hard to make analytics ‘instant’, where we effectively eliminate the perception of latency so users can interactively explore their data to find the proverbial needle-in-the-haystack, without waiting minutes, hours or even days for their results. The solutions of the past—to throw more hardware at the problem, or to take insight-limiting shortcuts via pre-aggregation or downsampling, are not the answers for today, much less tomorrow. Our goal is to give our customers a competitive advantage through painstakingly optimizing our software to take full advantage of modern hardware, particularly the massive parallelism of GPUs. Obsession with shaving off milliseconds is a particular quirk of our culture, and yet simultaneously existential, as it is ultimately the source of the differentiated value we deliver our customers and open source community.
Second, ‘power’ relates to all the things a user can do with our product. For some users, this could mean enabling advanced geospatial analytics at unprecedented scale, for others it might mean the ability to visually join and cross-filter multiple datasets in a single dashboard. "Powerful" is inherently contextual, but directionally for us it means enabling analysts and data scientists to dive deeper into their data than they previously thought possible. Our use of GPUs provides us with a distinct advantage here, as they are the singular hardware platform to combine massive computational and memory bandwidth with an incredibly optimized native rendering pipeline, the raw ingredients that enable the magic our customers have come to depend on. Of course, as with all mission statements, making analytics powerful is still deeply aspirational for us, and both our near and long-term roadmaps are deeply oriented to enabling our users to dive deeper and discover more with our platform.
Third, we believe it is far too difficult to access, stand-up and use high-performance analytics systems. At OmniSci we want to make the experience with our platform ‘effortless’, whether it’s installing our software, accessing our cloud offering, ingesting data, building dashboards, or exploring data as an analyst. One could liken a lot of enterprise systems to buying a mobile phone 20 years ago - hard to buy, hard to set-up, and hard to use. Think of the massive complexity around setting up, maintaining, and ingesting data and running analytics on one of today’s big data solutions. It involves purchasing or cloud provisioning potentially hundreds of nodes, ensure availability of spares for inevitable faults or network loss, intense data architecting/modeling (including determining how the data should be cubed, indexed, sharded, etc.), and perhaps setting up hot in-memory caches of common views of the data to prevent the whole cluster from becoming gridlocked when too many users want to query the system at once.
In contrast, OmniSci users typically achieve immense performance at scale on one or a handful of nodes, do not need to pre-aggregate, index, downsample, or otherwise perform modeling or pre-computation on their data, and typically can build their own dashboards on data that they, not IT or data engineering, ingest themselves. One of our customers was able to stand up the OmniSci platform on their DGX workstation in less than thirty minutes, ingest nearly 500M records in less than a minute, and were interactively exploring that data in ways previously unimaginable. Our vision is to make using OmniSci like using a new mobile today: open the packaging, turn it on and get started. We have a lot more to do in this vein, but codifying this in our mission statement indicates how important this is to us.
When a company raises a substantial amount of capital many people ask “what will the money be used for?” This is where I want to touch on our core values.
The first is technological leadership. We believe we have built the most advanced system of its kind in the market, but we cannot rest here. The number one priority for OmniSci’s next chapter is to accelerate innovation by significantly expanding our research and development teams. We are determined to increase our technology leadership of this market because we believe that superior products ultimately win in markets that undergo significant disruption.
Next, we need to expand our organization, methodically and thoughtfully, here in the US and key international markets. We have growing, active demand, fueled by our open source and cloud offerings, where large organizations have been using our software and now want more support as they expand their usage across their enterprises. As we look to hire the right people for OmniSci, our four other core values are vital for us. We look for passion, humility, different thinking, and a ‘day one’ attitude. We have an awesome culture of celebration and camaraderie at OmniSci, coupled with a recognition that we are doing serious things for serious organizations, often with mission critical outcomes. Hiring great people that embody our core values is essential to delivering for our customers.
To finish, some sincere thanks: none of what we’ve achieved so far would be possible without the tremendous support of our investors, board of directors, advisors and partners; and our customers and open source community who push us to be better on every front. However, above all, it’s the incredible OmniSci team that I want to thank the most. Every day I come to work excited about what we will do together that day. I am honored to work alongside such a tremendously smart, passionate, and humble group of people.
CEO & Co-Founder