Qubole has built a Hadoop managed service on AWS that allows its customers to focus on deriving the most business value from their data without worrying about building new infrastructure and hiring new staff to run it, writes Wikibon Principal Research Contributor Jeff Kelly in “Qubole Tries to Up-level the Hadoop Conversation with Managed Cloud Service“. Cofounded by Hive creator Ashish Thusoo, the service provider wants to help companies conquer the bottlenecks of the upfront costs of hardware and expert staff, complexity of deploying and maintaining Hadoop clusters and related software, and of recruiting and keeping rare Big Data infrastructure pros.

To learn more about Big Data tools, vendors, and services, watch theCUBE’s coverage of its own event, BigDataSV 2014, February 11-13 on SiliconAngle.tv.

Its Qubole Data Service (QDS) has more than a dozen data connectors for importing and exporting data to and from the platform. The core is Qubole’s managed Hadoop platform, including Hive, Sqoop, Pig and Oozie and an SK for building applications in Python. It recently added Presto, an open-source project supporting SQL-style analytics on Big Data, created by Facebook, which says it is orders of magnitude faster than Hive, returning query results in milliseconds. Hadoop clusters include auto-scaling. MapReduce job and SQL-style queries can be created on an interactive GUI.

It has more than 50 customers, mostly online-native companies including digital marketing firms, SaaS vendors and online retailers. It is used mostly by data architectures and data scientists and is not designed to support interactive Big Data applications deployed to large numbers of concurrent business users.

The benefits of a service like QDS, Kelly writes, are the elimination of capital expenditures on hardware and challenges of hiring and retaining scarce Big Data practitioners. This allows users to focus on gaining actionable insights from data. But it requires users to move critical data to the public cloud, specifically in this case AWS, where security and SLA delivery is not always ideal.

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