Imply Data: $100 Million Funding And $1.1 Billion Valuation

By Noah Long ● May 24, 2022
  • Imply Data recently announced it raised $100 million in Series D funding at a valuation of $1.1 billion. These are the details.

Imply Data – a company founded by the original creators of Apache Druid – recently announced its $100 million Series D financing, which values the company at $1.1 billion. This funding round was led by Thoma Bravo with participation from OMERS Growth Equity, both new investors.

Existing investors Bessemer Venture Funds, Andreessen Horowitz, and Khosla Ventures also participated in the financing. This funding round brings Imply’s total funding raised to date to $215 million as the company accelerates to meet the growing need for modern analytics applications.

The demand for Imply is driven by an industry evolution in analytics led by software developers. And for decades, analytics have been confined to static executive dashboards and reports powered by batch-oriented data warehouses. Plus leading companies are turning to their developers to build analytics applications that deliver interactive data experiences from streaming data and deliver real-time insights to both internal and external users. And developers at thousands of companies have turned to Apache Druid, the leading real-time analytics database.

This new funding round will enable Imply to accelerate its mission to help developers become the new heroes of analytics. And the funding round is the latest milestone solidifying Imply’s position as the industry leader in this emerging category. Plus it follows the recent product and open source innovation announced in March — specifically, the launch of Imply Polaris, the fully-managed DBaaS built from Apache Druid, and the introduction of a new multi-stage query engine that makes Druid the only database to support advanced reports and complex alerts alongside interactive, real-time analytics.

As a leading contributor to Apache Druid, Imply essentially delivers the complete developer experience for Druid as a fully-managed DBaaS (Imply Polaris), hybrid-managed software offering (Imply Enterprise Hybrid), and self-managed software offering (Imply Enterprise). And the company builds on the speed and scalability of Apache Druid with committer-driven expertise, effortless operations, and flexible deployment to meet developers’ application requirements with ease. Organizations trust Imply’s technology to play a key role in their internally-facing and customer-facing solutions and services.

KEY QUOTES:

“In its early days, Druid was adopted for a set of use cases in a handful of industries. Today, developers have shown its applicability across all industries—and the use cases have expanded exponentially. It’s humbling to see how Apache Druid and Imply have been so instrumental in helping our customers create competitive advantages.”

– Fangjin “FJ” Yang, CEO and co-founder of Imply, and co-creator of Apache Druid

“We’re excited to lead Imply’s Series D. FJ and his team are at the cusp of a market evolution in analytics, opening up a whole new world of analytics use cases and economic value. It was clear from the beginning of our relationship that we would enjoy a strong partnership with management, and they very much appreciated the level of experience we bring to the table as software-specialist investors over the last 20 years.”

– Robert (Tre) Sayle, a partner at Thoma Bravo

“As analytics adoption continues to accelerate, software developers are demanding more real-time solutions with Apache Druid and Imply leading the category. We’re thrilled to partner with FJ and the pioneering team of inventors at Imply as they continue to build on their category leadership by driving innovation and expanding analytics use cases.”

– Warda Shaheen, co-head of software at OMERS Growth Equity

“Providing advertisers with full transparency on engagement is a top priority. To do this, we need instant access to reports and data-driven tools. By using Apache Druid and Imply, we can ingest multiple events straight from Kafka and our data lake, ensuring advertisers have the information they need for successful campaigns in real-time.”

– Shariq Rizvi, executive vice president of ads monetization at Reddit

“As the leader in digital trust & safety, we enable online businesses to prevent fraud and abuse while streamlining customer experiences. We built an anomaly detection engine called Watchtower, which uses machine learning models to detect unusual activity. Apache Druid and Imply help us analyze data with an interactive experience that provides us with on-demand analysis and visualization.”

– Neeraj Gupta, SVP of engineering and cloud operations at Sift

“In order for Natural Intelligence to effectively match high-intent consumers with leading brands, it’s critical we capture and understand millions of end-to-end user interactions. This is why we have chosen Apache Druid and Imply—to be able to understand massive amounts of data in near real-time, from the ads consumers watch, through the entire decision-making process to ultimately power better and more personalized marketing campaigns.”

– Lior Schachter, CTO of Natural Intelligence

“Our platform enables enterprise teams to successfully deploy AI models and avoid AI failures by analyzing massive amounts of data telemetry to detect anomalies and performance regressions in real-time. That’s why we chose Apache Druid and Imply to power our dynamic query engine. We combine both stream and batch processing, empowering our customers to interactively explore limitless amounts of statistical data profiles, metrics and anomalies across their data and machine learning pipelines.”

– Andy Dang, co-founder and head of engineering at WhyLabs, the leading AI observability company

“It’s a breath of fresh air to see Imply expanding analytics use cases beyond business intelligence and reporting. While others are simply modernizing infrastructure for decades old workloads, Imply is blazing a new trail for real-time, analytics applications.”

– Eric Kavanagh, CEO and co-founder, The Bloor Group

Exit mobile version