Analytics market leader Imply raises $70 million Series C

Bessemer Venture Partners leads the recent growth round for Imply to accelerate its mission of delivering value from data in real-time.

Data is codified everywhere—from the workplace to our homes, and it's being generated at an unprecedented pace, making real-time analytics a business imperative. As digitization has accelerated substantially over the past decade, so too has the complexity of core big data attributes. The variety (diverse sources), veracity (ensuring authenticity), and volume (increasing amounts) of data are well-recognized, however, a lesser-known and fourth attribute is velocity, the frequency at which companies need to process incoming data.

Whether banks need immediate business intelligence to monitor transaction activity and identify fraud, or a network company leverages telemetry data to understand saturation points and get alerts when services are down, companies depend on analytics to stay responsive and maintain their competitive advantage.

The brain trust and creators of Druid — Fangjin “FJ” Yang, Vadim Ogievetsky, and Gian Merlino — foresaw the rising demand for real-time analytics, and so after their meaningful contributions to Druid’s open source community, they commercialized the project by founding Imply Data. When we first met FJ, Vadim, and Gian, we were immediately impressed by their technical prowess and deep sense of empathy for the customer problems they striving to solve. As we got to know the founders more over time we saw that they were not only building a transformative company with strong customer evangelism but also were doing it the right way. The team leads with integrity, building a values-driven organization, powered by gusto and ambition. We were compelled to invest and lead Imply’s $70 million Series C financing.

“As the cloud data stack continues to evolve, what worked yesterday isn’t going to work for insights-driven businesses of tomorrow,” shared CEO and Co-founder Fangjin “FJ” Yang. “At Imply, we’re pioneering a new category — analytics-in-motion — which is highly scalable, cost-effective, and helps teams get to that ‘a-ha’ moment, faster than ever before.”

For example, GameAnalytics, one of Imply’s customers and a leading provider of analytics in the mobile gaming space, leverages analytics-in-motion to provide robust reporting features. "We wanted to build a customer-facing analytics application that combined the performance of pre-computed queries with the ability to issue arbitrary ad-hoc queries without restrictions," said Ioana Hreninciuc, CEO of GameAnalytics. “We selected Imply and Druid as the engine for our analytics application, as they are built from the ground up for interactive analytics at scale.”

The number of data infrastructure tools available has evolved over the years to reflect the proliferation of data itself, but no tool has been as optimized to handle real-time analytics as Druid, the foundation of Imply’s solution. As a high-performance online analytical processing (OLAP) database, Druid can ingest vast amounts of data, provide low latency queries, and scale tremendously. As a result, real-time data can be queried as soon as available alongside historical data with low latency. This sort of rapid, high-volume query capability is something that many other traditional data tools cannot do well-given core infrastructure and computational limitations.

At Bessemer, we’ve had the privilege of partnering with bold teams leading the charge on technology evolutions. We have witnessed the increasing growth of the real-time analytics market, and with the explosion of data and devices globally showing no signs of stopping, we expect this trend to continue for years to come. As the modern data stack evolves, customers will prefer tools with more specialization, optimized for their business-critical use cases. Imply is at the forefront of this movement and we are excited to partner with FJ, Vadim, Gian, and the rest of their groundbreaking team as they forge ahead on their mission to accelerate the delivery of value from data in real-time.