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Alluxio - Open Source Memory Speed Virtual Distributed Storage

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Original source (www.alluxio.org)
Tags: storage hadoop spark alluxio tachyon
Clipped on: 2018-05-29

Open Source Memory Speed Virtual Distributed Storage

Alluxio, formerly Tachyon, enables any application to interact with any data from any storage system at memory speed.

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New and Upcoming

MOMO: Accelerating Ad Hoc Analysis with Spark SQL and Alluxio · Haojun (Reid) Chan, Wenchun Xu · Mar 20, 2018

Announcing the Release of Alluxio Enterprise Edition and Community Edition v1.7.0 · Andrew Audibert, Calvin Jia, Gene Pang & Adit Madan · Feb 2, 2018

Storage Unification and Abstraction

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As one of the largest Internet companies in the world, Baidu constantly faces the challenges of managing data at multi-petabyte scale. By adopting innovative technologies like Alluxio we are able to help our users extract meaningful and useful data almost instantly. Our deployment of an Alluxio cluster has already reached 1,000 workers, which is one of the largest Alluxio clusters in the world. The tiered storage of Alluxio has provided us great flexibility in managing data in large-scale. We are seeing an average 10-fold, and up to 30-fold performance improvement in supporting interactive query system and other types of workloads. This greatly improved the speed in making important business decisions.

Michael Franklin

Director of the AMPLab at UC Berkeley

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Alluxio is the next project with roots in the AMPLab to have major impact. We see it playing a huge disruptive role in the evolution of the storage layer to handle the expanding range of big data use cases.

Wensong Zhang

CTO and Senior Research Fellow of Alibaba Cloud, founder of Linux Virtual Server

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As the cloud computing business for Alibaba Group, the world’s leading e-commerce business, Alibaba manages many of the world’s largest data centers, including the largest big data cluster ever built in China. With Alluxio combined with AliCloud OSS as well as other AliCloud cloud service products, our customers can leverage the technology trends of hardware to run important jobs at the fastest performance. We have been contributing to the Alluxio open source community and believe that Alluxio will play a critical role in the future of big data infrastructure.

Ion Stoica

Professor at UC Berkeley, co-author of Spark, co-founder and executive chairman of DataBricks, co-director of UC Berkeley AMPLab

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As a layer that abstracts away the differences of existing storage systems from the cluster computing frameworks such as Apache Spark and Hadoop MapReduce, Alluxio can enable the rapid evolution of the big data storage, similarly to the way the Internet Protocol (IP) has enabled the evolution of the Internet.

Michael Greene

Intel Vice President

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Big data analytics is driving new requirements for distributed memory across clusters for real-time streaming, interactive queries, analytics and graph processing. We are excited to work with developer communities on Alluxio and to optimize Alluxio solutions on Intel platforms. Ultimately, this helps our customers create more innovative and high performance cloud and big data solutions.

James Peng

Baidu Chief Architect

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As one of the largest Internet companies in the world, Baidu constantly faces the challenges of managing data at multi-petabyte scale. By adopting innovative technologies like Alluxio we are able to help our users extract meaningful and useful data almost instantly. Our deployment of an Alluxio cluster has already reached 1,000 workers, which is one of the largest Alluxio clusters in the world. The tiered storage of Alluxio has provided us great flexibility in managing data in large-scale. We are seeing an average 10-fold, and up to 30-fold performance improvement in supporting interactive query system and other types of workloads. This greatly improved the speed in making important business decisions.

Michael Franklin

Director of the AMPLab at UC Berkeley

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Alluxio is the next project with roots in the AMPLab to have major impact. We see it playing a huge disruptive role in the evolution of the storage layer to handle the expanding range of big data use cases.

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