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“This solution breaks new ground for the world of big data,” said John Engates, CTO, Rackspace. “For the first time, Hadoop and Spark can have the best of both worlds: bare metal performance with cloud agility, all backed by Fanatical Support®.”
To give the big data community hands-on experience with this new generation of bare metal data science, Rackspace is offering a $250 promotional credit towards the first two months of service.
OnMetal Cloud Big Data Platform is a turn-key service, which eliminates the need to configure and integrate complex hardware and software infrastructure. Senior business leaders now have a simple alternative for implementing their big data agendas. The beta launch of support for Apache Spark also offers companies the tools needed to accelerate the development and analysis of data science applications. For instance, developers can interact with data in real time via Scala or Python Shells. And with the inclusion of high level tools like Spark SQL, Spark Streaming, MLib and GraphX, developers and data scientists can now take advantage of the most powerful tools from Spark for streaming, machine learning, and graph-optimised applications.
Highlights include:
· Big Data as a Service – The solution offers a Hadoop and Spark hardware and software stack with the elasticity and availability of the Rackspace Managed Cloud. This saves customers time and money in deploying, maintaining and scaling Big Data workloads.
· Rapid Time to Market – Data Scientists and decision makers can now launch a big data platform in three clicks, saving significant time, money and resources. Once deployed, developers can leverage Spark to rapidly write applications using Java, Scala or Python and use Spark interactively from the Scala and Python shells.
· Breakthrough Performance –OnMetal Cloud Big Data for Spark is engineered for break-through performance, enabling data scientists to iterate with large data sets. With Spark, beta customers can now leverage the speed of memory optimised processing to accelerate data discovery. In preliminary DFSIO and Terasort performance benchmark testing for OnMetal Cloud Big Data platform, results show an average of 50 to 100% improvement from the standard Cloud Big Data Platform instance at Rackspace.
With this announcement, Rackspace continues to expand the breadth and capability of its portfolio of managed databases, now supporting the most popular Big Data, SQL, and NoSQL databases. This includes Hadoop, Spark, MongoDB, Redis, Oracle, Microsoft SQL Server, MySQL, Percona, and MariaDB. Customers have the flexibility to deploy across private, public, bare metal and hybrid clouds with options to automate and reduce the time and money needed to deploy, scale, manage and help ensure the availability of production database applications.
“Enterprises are showing increasing interest in the value provided by the large-scale data processing that Hadoop and Spark can provide, but can be wary of the upfront cost and complexity of setting up a cluster to prove that value,” said Matt Aslett, research director, data platforms and analytics, 451 Research. “Managed services such as this enable enterprises to focus their energies on generating business insights rather than configuring and managing infrastructure."
