Cloudera Reports $79.6M in First Quarter Revenue After IPO

Sean Michael

Updated · Jun 09, 2017

Big Data vendor Cloudera had its Initial Public Offering (IPO) on April 28 and on June 8 reported its first quarterly earnings as a public company.

For the quarter, Cloudera reported revenue of $79.6 million, which is a 41 percent year-over-year increase. Cloudera didn’t generate a profit on that revenue, instead it reported a net loss of $222.3 million, up substantially from the $43.5 million it lost in the first quarter of last year.

Looking forward, Cloudera provided second quarter guidance for revenue to be in the range of $85 to $86 million, representing 32 to 33 percent year-over-year growth.

“Cloudera is helping to solve some of the world’s biggest problems with data,” Tom Reilly, Chief Executive Officer at Cloudera, said during his company’s earnings call. “Our modern platform for machine learning advance analytics empowers organization to collect store and act on vast amount of data from a variety sources including the Internet of Things to transform their businesses.”

Cloudera’s platform expanded in the first quarter with several new projects and commercial products. The Apache Kudu open source data store effort was launched which helps to round out the broader Hadoop Big Data offering that includes 26 projects Cloudera helps to develop.

“We don’t see any substantial feature gaps that would encourage us to go fill in with more projects,” Mike Olson, co-founder of Cloudera said. ” So we’ll watch the innovation going on in the space and certainly if there are new developments we may pull in more projects.”

“In general, I think the addition of Kudu has closed a gap that we needed to close, we can now take on IoT, time series and relational were close that were hard for us to address prior and run some high-performance analytics including machine learning on that and so I think that’s a pretty good for us,” he added.

During the quarter Cloudera also released its Altus data engineering product. Olson explained that a large amount of enterprise data analytics is data ingest, prep, organization and cleaning. “We’ve built an as a service offering where we manage that service and allow our customers to use those services very, very simply,” Olson said.

Sean Michael Kerner is a senior editor at EnterpriseAppsToday and Follow him on Twitter @TechJournalist.

Sean Michael
Sean Michael

Sean Michael is a writer who focuses on innovation and how science and technology intersect with industry, technology Wordpress, VMware Salesforce, And Application tech. TechCrunch Europas shortlisted her for the best tech journalist award. She enjoys finding stories that open people's eyes. She graduated from the University of California.

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