Distributed file system for cloud: Difference between revisions

Revision as of 01:50, 9 January 2019

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==== Other examples ====

Distributed file systems can be optimized for different purposes. Some, such as those designed for internet services, including GFS, are optimized for scalability. Other designs for distributed file systems support performance-intensive applications usually executed in parallel.<ref>{{harvnb|Soares| Dantas†|de Macedo|Bauer|2013|p=158}}</ref> Some examples include: [https://www.elastifile.com Elastifile Cloud File System], [[MapR FS|MapR File System]] (MapR-FS), [[Ceph (storage)|Ceph-FS]], [[BeeGFS|Fraunhofer File System (BeeGFS)]], [[Lustre (file system)|Lustre File System]], [[IBM General Parallel File System]] (GPFS), and [[Parallel Virtual File System]].

Elastifile Cloud File System is a distributed file system designed for the public cloud. It supports enterprise features (e.g. snapshots, high availablity) and is optimized to deliver the ease-of-use, scalability, performance, and reliability required to support enterprise applications and workflows. It supports automated data tiering between file and object storage and can be used as scalable, persistent storage for Kubernetes deployments. <ref>{{Cite web|url=https://www.zdnet.com/article/google-adds-elastifile-to-cloud-arsenal/|title=Google adds Elastifile to cloud arsenal|last=Harris|first=Robin|website=ZDNet|language=en|access-date=2019-01-09}}</ref><ref>{{Cite web|url=https://cloud.google.com/customers/esilicon/|title=eSilicon Corporation Case Study|website=Google Cloud|language=en|access-date=2019-01-09}}</ref><ref>{{Cite web|url=https://cloud.google.com/solutions/partners/elastifile-cross-cloud-data-fabric|title=Deploying the Elastifile Cross-Cloud Data Fabric {{!}} Solutions|website=Google Cloud|language=en|access-date=2019-01-09}}</ref>

MapR-FS is a distributed file system that is the basis of the MapR Converged Platform, with capabilities for distributed file storage, a NoSQL database with multiple APIs, and an integrated message streaming system. MapR-FS is optimized for scalability, performance, reliability, and availability. Its file storage capability is compatible with the Apache Hadoop Distributed File System (HDFS) API but with several design characteristics that distinguish it from HDFS. Among the most notable differences are that MapR-FS is a fully read/write filesystem with metadata for files and directories distributed across the namespace, so there is no NameNode.<ref name="mapr-productivity">{{cite web|last1=Perez|first1=Nicolas|title=How MapR improves our productivity and simplifies our design|url=https://medium.com/@anicolaspp/how-mapr-improves-our-productivity-and-simplify-our-design-2d777ab53120#.mvr6mmydr|website=Medium|publisher=Medium|accessdate=June 21, 2016}}</ref><ref>{{cite web|last1=Woodie|first1=Alex|title=From Hadoop to Zeta: Inside MapR’s Convergence Conversion|url=http://www.datanami.com/2016/03/08/from-hadoop-to-zeta-inside-maprs-convergence-conversion/|website=Datanami|publisher=Tabor Communications Inc.|accessdate=June 21, 2016}}</ref><ref>{{cite web|last1=Brennan|first1=Bob|title=Flash Memory Summit|url=https://www.youtube.com/watch?v=fOT63zR7PvU&t=1682|website=youtube|publisher=Samsung|accessdate=June 21, 2016}}</ref><ref name="maprfs-video">{{cite web|last1=Srivas|first1=MC|title=MapR File System|url=https://www.youtube.com/watch?v=fP4HnvZmpZI|website=Hadoop Summit 2011|publisher=Hortonworks|accessdate=June 21, 2016}}</ref><ref name="real-world-hadoop">{{cite book|last1=Dunning|first1=Ted|last2=Friedman|first2=Ellen|title=Real World Hadoop|date=January 2015|publisher=O'Reilly Media, Inc|___location=Sebastopol, CA|isbn=978-1-4919-2395-5|pages=23–28|edition=First|url=http://shop.oreilly.com/product/0636920038450.do|accessdate=June 21, 2016|language=English|chapter=Chapter 3: Understanding the MapR Distribution for Apache Hadoop}}</ref>