Dr. Yu Xu of TigerGraph

An exclusive Tech Tribune Q&A with Dr. Yu Xu, the founder and CEO of TigerGraph, which was honored in our:
Tell us the origin story of TigerGraph – what problem were you trying to solve and why?

In 2012, I realized the best up and coming internet companies were not only powered by internal graph technology, but also betting big on graph. Twitter was big on the interest graph, Google launched a knowledge graph (and its famous PageRank algorithm was based on graph too), Facebook owned the social graph, and LinkedIn was in rapid expansion mode, later becoming the world’s professional network graph.

However, there were no performant graph products on the market for other companies to use in 2010, the year that companies really started to focus on data collection. I believed early on that graph would also benefit companies across verticals, not just internet companies. So, our startup was founded to provide a general-purpose, high performance, real-time and distributed graph database to power new applications for all businesses.

What was the biggest hurdle you encountered in your journey?

During each phase of our journey, we’ve encountered different challenges. In the early days, we focused more on educating prospects as to why a new type of database was needed, which sometimes proved to be difficult. However, through continuous communication on what use cases were best suited for a graph database, we were able to educate the market and breakthrough. Nowadays, our internal hurdles are focused more on asking how to shorten sales cycles with large enterprises and navigate through long and complex procurement processes.

What does the future hold for TigerGraph?

Graph is one of the fastest growing categories among databases, with industry analyst firm Gartner forecasting 100% annual growth through 2022. TigerGraph, which was launched out of stealth mode in late 2017 with the leading third-generation graph database and the only distributed graph database on-prem/in the cloud, has been in hyper-growth mode ever since. We have the largest graph deployments across the world and we are fortunate enough to have some of the world’s largest customers choosing our technology across several verticals, including JPMC, United Healthcare Group, Visa, Intuit, HBO, Duke Energy, and AT&T. They use it to help improve patient care and reduce healthcare cost, fight fraud, minimize power outage, and improve customer experience.

In the future, our ongoing goal is to help our customers improve the world with advanced analytics. Many of these customers are using TigerGraph for database machine learning, another unique capability of our product, along with generating features based on graph analytics for supervised machine learning. This solves one of the industry’s biggest problems – improving the efficiency and accuracy of machine learning and delivering explainable artificial intelligence. Our future is bright, and we are committed to redefining graph databases as a new big category to benefit businesses across all sectors.

What are your thoughts on the local tech startup scene in Redwood City?

When I think back to the early 2000’s, it used to be that most technology startups were based in San Francisco or the South Bay. Today, we see more and more based in Redwood City, with many focused on infrastructure and big data. I believe Redwood City will continue to attract great technology startups for the foreseeable future.

What’s your best advice for aspiring entrepreneurs?

When you lead a product-oriented company, my best advice would be to not underestimate the time and patience needed to develop high-quality software. Invest in the necessary time required to create and perfect a sustainable product. You only have one chance to prove yourself and your technology to the masses, and you want to be certain you shine when you have the opportunity.

With TigerGraph, we took five years to develop our product. We developed it from the ground up, focusing on the best possible performance, scalability, and ease of use. The high performance and quality of our work really helped us be successful with customers. In addition, we became the leader in the graph database market (today), despite the fact that we were not the first player in a very competitive database landscape.


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