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Wednesday, November 16, 2016

Hortonworks prescribes cloudy Hadoop for AWS

#Hortonworks is launching a new cloud service on #Amazon Web Services for customers who don't fancy working on #Azure. Hortonworks Data Cloud is now available on #AWS, offering users the ability to quickly spin up a #Hadoop cluster in the cloud, using Hortonworks Data Platform ( #HDP ) through the flexible billing options of the AWS Marketplace. Comfortable with its existing experience of running HDP clusters on AWS – with more than a quarter of Hortonworks' customer base having a cloud footprint alongside their on-premise machines – the Hadoop vendor is now targeting those more prescriptive, one-ramp use cases. With that prescriptive experience pre-configured and pre-tuned for what Hortonworks expects will be the most popular use cases – ie, data science and exploration, data preparation and ETL, data analytics and reporting – data scientists, developers and end users will be more productive. Hortonworks Data Cloud is particularly designed to take advantage of how potential customers will use AWS, specifically targeting ephemeral workloads that will need to integrate with AWS services such as Amazon S3, RDS and EC2. With a five-year partnership with Microsoft ongoing, Hortonworks will continue to offer HDInsight on Azure. HDInsight is a managed service, with the upgrades handled under the hood, and is "deeply integrated with Azure as a first-class Microsoft service." "We are enabling modern applications on a connected data architecture and believe customers should have a consistent data experience across cloud and data center," said Shaun Connolly, chief strategy officer at Hortonworks. "Hortonworks Data Cloud for AWS gives customers an on-demand cloud service for a prescriptive experience for the most common Hadoop, Spark and Hive use cases, with community support and the flexibility of hourly and annual billing through existing AWS Marketplace accounts."

http://www.theregister.co.uk/2016/11/15/hortonworks_flings_cloudy_hadoop_at_aws/

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