Analytics Startup RapidMiner Nets $15M Round

Company aims to simplify predictive analytics deployment for clients

John Rath

February 24, 2015

1 Min Read
Analytics Startup RapidMiner Nets $15M Round

Big data analytics startup RapidMiner announced that it has raised $15 million to help it execute on aggressive growth plans. The Series B round was co-led by Ascent Venture Partners and Longworth Venture Partners.

RapidMiner has taken a strong position in the analytics market and describes its offering as code-free predictive analytics, with pre-built models and one-click deployments. Gartner placed this small startup from Cambridge in the leaders quadrant alongside IBM and SAS for Advanced Analytics Platforms. RapidMiner reports that in the last year the company tripled product revenues, grew to over 250,000 active users, and secured dozens of net new customers and strategic partnerships.

"RapidMiner is the only code-free predictive analytics solution on the market that can execute analytical processes in-memory, in-Hadoop, in-cloud, in-stream, and in-database," Nilanjana Bhowmik, partner at Longworth Venture Partners, said in a statement. "We’re consistently seeing the RapidMiner team push the envelope and look ahead at what its community of users need for accurate business decisions, making it the dominant leader of the next generation of modern analytics platforms."

The analytics startup offers free and commercial versions of its products.

Just before to the funding announcement RapidMiner launched enhancements to its platform with pushdown analytics computation for big data in Hadoop. The company says that using with pushdown Hadoop processing in RapidMiner Radoop, it can push the computation of more than 250 machine learning models directly to the data in the cluster.

"Many companies are still deterred by the complexity of building analytics applications on a complicated big data technology stack," Nik Rouda, senior analyst at ESG, said in a statement. "RapidMiner is differentiated both by offering a solution that is very deep and yet still user-friendly, attributes which will enable faster development in a wide range of environments."

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