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NetApp Acquires Startup Data Mechanics for Spark Analytics

The acquisition will enable customers to optimize using Apache Spark on the Kubernetes platform.
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Written by Chris Preimesberger on

All-purpose data storage provider NetApp revealed June 22 that it has acquired startup Data Mechanics, which provides enterprise-scale data processing and cloud analytics through its own cloud-based platform. Financial details of the transaction were not disclosed.
Data Mechanics, privately held and headquartered in San Francisco, enables businesses to capitalize on Apache Spark, an open-source unified analytics engine for fast large-scale data processing and machine learning, on the Kubernetes platform. Spark provides a universal interface for programming entire server clusters with data parallelism and fault tolerance for high-speed transactions.
 
Kubernetes is an open-source container-orchestration system for automating computer application deployment, scaling and management. 
 
Sunnyvale, Calif.-based NetApp, which started out as a storage hardware company in 1992, has been adapting its hardware and software into cloud services for the last decade. It now has added next-generation containers, microservices, analytics and machine learning to its product set, so that users can more quickly evaluate a storage system's operating efficiencies and automate manual processes.
 
Two-year-old Data Mechanics provides NetApp with a part of the next-gen storage puzzle it lacked: a way to make it simpler and more cost-effective for IT across all industries to fully leverage Apache Spark and the Kubernetes platform to advance their data and cloud initiatives, NetApp Senior Vice-President Anthony Lye told ZDNet.

The acquisition comes less than a year after NetApp acquired Spot (now Spot by NetApp), a CloudOps provider that automates and optimizes workloads running in public cloud environments. Lye said Data Mechanics' staff and IP will be integrated with the Spot by NetApp team and portfolio to accelerate the development of NetApp's recently announced Spot Wave storage package, which simplifies, optimizes and automates Spark workloads running in public clouds.

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