Loading...
You are here:  Home  >  Data Education  >  Big Data News, Articles, & Education  >  Big Data News  >  Current Article

Hortonworks Data Platform 3.0 Enables Containerization and Deep Learning Workloads

By   /  June 21, 2018  /  No Comments

Hortonworks, Inc.® (NASDAQ: HDP), a leading provider of global data management solutions, announced in a recent press release “the Hortonworks Data Platform (HDP) 3.0, which delivers significant new enterprise features including containerization for faster and easier deployment of applications, and increased developer productivity. The new version of HDP enables customers to more quickly, reliably and securely get value from their data at scale to drive business transformation.”

“The pace of innovation coming from the open source community has not slowed and means that customers are getting the latest and best new features in HDP, including containerization, the ability to run deep learning applications and major performance enhancements to analytics,” said Arun Murthy, co-founder and chief product officer, Hortonworks. “HDP is maturing to meet changing enterprise requirements, and we are pleased to deliver this landmark release to customers so they can embrace a modern data architecture.”

“A key component of modern data architectures, HDP is a secure, enterprise-ready, open source Apache™ Hadoop®-based platform. It addresses the complete needs of data at rest, powers real-time customer applications and delivers robust big data analytics that accelerate decision-making and innovation. Unlike other Hadoop-based distributions, many of the new enhancements to HDP 3.0 are based on Apache Hadoop 3.1 and include:

Agile application deployment via containerization, which enables apps to be launched quickly, allowing users to save time and resources. With containers running on HDP, developers can move fast, deploy more software efficiently and operate with increased velocity.”

Read more at PR Newswire.

Photo credit:Hortonworks, Inc

You might also like...

Thinking Inside the Box: How to Audit an AI

Read More →