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MapR Announces Clarity Program for Cloudera and Hortonworks Customers with New Platform Update and Free Data Assessment Service

MapR® Technologies, Inc., provider of the data platform for AI and Analytics, announced the Clarity Program, a new product release and a free assessment service that provides a comprehensive understanding of a customer’s current data environment and the best practices to achieve a clear path to support AI, cloud, containers and IoT deployments.

Cloudera + Hortonworks: A Marriage from the Edge to AI

Did you hear the clap of thunder in the big data ecosystem today? If so, it was only just Cloudera, Inc. and Hortonworks, Inc. jointly announcing that they have entered into a definitive agreement under which the companies will combine in an all-stock merger of equals. The transaction, which has been unanimously approved by the Boards of Directors of both companies, will create the world’s leading next generation data platform provider.

Hadoop-as-a-Service: The Need Of The Hour For Superior Business Solutions

In this contributed article, content writer Swamini Kulkarni discusses how the launch of new platforms based on HaaS solutions demonstrate that Hadoop-as-a-Service (HaaS) is a promising solution for building and managing the big data cluster, which will compel organizations to consider Hadoop as a potential solution for big data challenges.

Interview: Jamie Engesser, VP Product Mangement at Hortonworks

I recently caught up with Jamie Engesser, VP Product Mangement at Hortonworks during the company’s DataWorks Summit 2018 conference in San Jose, California, to get an update on his company’s direction and his sense for the pulse of the big data industry.

Hortonworks Data Platform 3.0 Enables Containerization and Deep Learning Workloads

Hortonworks, Inc.® (NASDAQ: HDP), a leading provider of global data management solutions, today announced 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.

Big Data, Hadoop & Cloud: Tackling a Chain of Emerging Challenges

In this special guest feature, Chandra Ambadipudi, CEO of Clairvoyant, provides a compelling tour de force through the recent history of the big data industry and how Hadoop and the cloud have made steady acceleration possible. Also offered are recommendations for how to address several challenges faced by enterprises with respect to big data cloud implementations.

Hadoop 3.0 Perspectives by Hortonwork’s Hadoop YARN & MapReduce Development Lead, Vinod Kumar Vavilapalli

In the Q&A below, , Hortonwork’s Hadoop YARN & MapReduce Development Lead, Vinod Kumar Vavilapalli, offers his perspectives on the recent release of Hadoop 3.0, the latest version of the Open Source software framework for reliable, scalable, distributed computing.

AtScale Brings its Universal Semantic Layer to the AWS Cloud

AtScale announced the preview availability of its universal semantic platform for business intelligence (BI) on Amazon Redshift. With this offer, enterprises will gain faster time to insight by deploying Big Data Analytics on the Amazon Cloud and benefit from an enhanced ROI by running production-ready workloads on the cost-effective Amazon cloud platform.

MapR Launches Managed Services for Improved DataOps

MapR Technologies, Inc., a pioneer in delivering one platform for all data, across every cloud, announced new Managed Services for the MapR Converged Data Platform. Available immediately, customers can focus on building a wide range of applications from analytics to machine learning and artificial intelligence (AI), while MapR manages the daily operations of the customer’s big data infrastructure from on-premises, across clouds and to the edge.

Business Lessons from Hadoop’s Non-Failure

In this special guest feature, Hiro Yoshikawa, co-founder and CEO of Treasure Data, counters the growing perception that Hadoop is a failure and focuses on the lessons that organizations can learn from the rush to adopt Hadoop.