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Items Tagged: data+lake

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Out on a data storage market limb: Six predictions for 2015

Our crystal ball tells us this will be a year of change for the data storage market.

  • Premiered: 01/05/15
  • Author: Mike Matchett
  • Published: Tech Target: Search Storage
Topic(s): TBA Data Storage TBA Storage TBA DAS TBA Big Data TBA data lake TBA hub concept TBA enterprise data TBA BlueData TBA hybrid storage TBA AFA TBA All Flash TBA all flash array TBA Data protection TBA cloud tiering TBA VM TBA Virtual Machine TBA Virtualization TBA VVOL TBA VMWare TBA EMC TBA NetApp TBA Avalanche Technology TBA HDS TBA Hitachi Data Systems TBA IBM TBA EVO:RAIL TBA Nutanix TBA Scale Computing TBA SimpliVity TBA hyperconverged
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Hadoop Storage Options: Time to Ditch DAS?

Hadoop is immensely popular today because it makes big data analysis cheap and simple: you get a cluster of commodity servers and use their processors as compute nodes to do the number crunching, while their internal direct attached storage (DAS) operate as very low cost storage nodes.

  • Premiered: 02/19/15
  • Author: Taneja Group
  • Published: Infostor
Topic(s): TBA Hadoop TBA Storage TBA DAS TBA Direct attached storage TBA Compute TBA SATA TBA HDFS TBA Hadoop Distributed File System TBA data TBA MapReduce TBA YARN TBA Hadoop 2 TBA data lake TBA data refinery TBA Enterprise Storage TBA DR TBA Disaster Recovery TBA compliance TBA Security TBA Business Continuity TBA Performance TBA FC TBA Fibre Channel TBA SAN TBA NAS TBA Virtualization TBA Cloud TBA VM TBA Virtual Machine TBA MapR
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Data lakes swim with golden information for analytics

First we had data. Then we had big data. Now we have data lakes. Will the murky depths prove bountiful?

  • Premiered: 04/14/15
  • Author: Mike Matchett
  • Published: TechTarget: Search Data Center
Topic(s): TBA data lake TBA analytics TBA Big Data TBA Mike Matchett TBA TechTarget TBA Hadoop TBA Business Intelligence TBA BI TBA OLAP TBA OLTP TBA NoSQL TBA SQL TBA Optimization TBA ETL TBA IoT TBA Internet of Things TBA MapR TBA Project Myriad TBA YARN TBA Virtualization TBA Business Continuity TBA Disaster Recovery TBA DR TBA BC TBA data swamp TBA BlueData TBA Dataguise TBA HDFS TBA Hadoop Distributed File System TBA IBM
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Navigate data lakes to manage big data

While the data lake concept appeals to business today, IT administrators must exercise caution prior to a full-scale implementation.

  • Premiered: 06/05/15
  • Author: Mike Matchett
  • Published: TechTarget: Search Storage
Topic(s): TBA data lake TBA Storage TBA Big Data TBA storage infrastructure TBA Data protection TBA big data lake TBA analysis TBA HDFS TBA Hadoop TBA Hadoop virtualization TBA Virtualization TBA Hadoop Distributed File System TBA software-defined TBA software-defined storage TBA BI TBA Business Intelligence TBA Disaster Recovery TBA Business Continuity TBA BC TBA DR TBA analytics TBA Spark TBA HP TBA Vertica TBA HP Haven TBA Haven TBA OLAP TBA data-aware
Profiles/Reports

Now Big Data Works for Every Enterprise: Pepperdata Adds Missing Performance QoS to Hadoop

While a few well-publicized web 2.0 companies are taking great advantage of foundational big data solution that they have themselves created (e.g. Hadoop), most traditional enterprise IT shops are still thinking about how to practically deploy their first business-impacting big data applications – or have dived in and are now struggling mightily to effectively manage a large Hadoop cluster in the middle of their production data center. This has led to the common perception that realistic big data business value may yet be just out of reach for most organizations – especially those that need to run lean and mean on both staffing and resources.   

This new big data ecosystem consists of scale-out platforms, cutting-edge open source solutions, and massive storage that is inherently difficult for traditional IT shops to optimally manage in production – especially with still evolving ecosystem management capabilities. In addition, most organizations need to run large clusters supporting multiple users and applications to control both capital and operational costs. Yet there are no native ways to guarantee, control, or even gain visibility into workload-level performance within Hadoop. Even if there wasn’t a real high-end skills and deep expertise gap for most, there still isn’t any practical way that additional experts could tweak and tune mixed Hadoop workload environments to meet production performance SLA’s.

At the same time, the competitive game of mining of value from big data has moved from day-long batch ELT/ETL jobs feeding downstream BI systems, to more user interactive queries and business process “real time” applications. Live performance matters as much now in big data as it does in any other data center solution. Ensuring multi-tenant workload performance within Hadoop is why Pepperdata, a cluster performance optimization solution, is critical to the success of enterprise big data initiatives.

In this report we’ll look deeper into today’s Hadoop deployment challenges and learn how performance optimization capabilities are not only necessary for big data success in enterprise production environments, but can open up new opportunities to mine additional business value. We’ll look at Pepperdata’s unique performance solution that enables successful Hadoop adoption for the common enterprise. We’ll also examine how it inherently provides deep visibility and reporting into who is doing what/when for troubleshooting, chargeback and other management needs. Because Pepperdata’s function is essential and unique, not to mention its compelling net value, it should be a checklist item in any data center Hadoop implementation.

To read this full report please click here.

Publish date: 12/17/15
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Scale-out architecture and new data protection capabilities in 2016

What are the next big things for the data center in 2016? Applications will pilot the course to better data protection and demand more resources from scale-out architecture.

  • Premiered: 02/17/16
  • Author: Mike Matchett
  • Published: TechTarget: Search Data Center
Topic(s): TBA scale-out TBA Data protection TBA DP TBA scale-out architecture TBA analysis TBA Data Center TBA data lake TBA Hadoop TBA hadoop cluster TBA cluster TBA Backup TBA Talena TBA HPE TBA 3PAR TBA flat backup TBA Snapshot TBA Snapshots TBA StoreOnce TBA Oracle TBA Oracle ZDLRA TBA ZDLRA TBA Zero Data Loss Recovery Appliance TBA converged TBA convergence TBA Cloud TBA backup server TBA Virtualization TBA Storage TBA Big Data TBA Lustre
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Assimilate converged IT infrastructure into the data center

With the hype around converged and hyper-converged IT infrastructure, resistance seems futile. While your IT organization will likely be a mix of converged, dedicated and cloud-based resources, convergence is moving into new areas.

  • Premiered: 03/16/16
  • Author: Mike Matchett
  • Published: TechTarget: Search Data Center
Topic(s): TBA convergence TBA Converged Infrastructure TBA Datacenter TBA Storage TBA converged TBA IT convergence TBA converged IT TBA Cloud TBA Public Cloud TBA OPEX TBA VCE TBA vBlock TBA Virtualization TBA software-defined TBA hyperconverged infrastructure TBA HCI TBA Nutanix TBA SimpliVity TBA Data protection TBA DP TBA Microsoft TBA StorSimple TBA Hybrid Cloud TBA Archive TBA Backup TBA BC TBA Business Continuity TBA Disaster Recovery TBA DR TBA data lake
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Galactic Exchange can get your Hadoop cluster up and running in just 5 minutes

Stealthy startup Galactic Exchange Inc. burst out of the shadows this weekend touting a new product that’s able to spin up an Hadoop or Spark cluster, ready to go, in just five minutes.

  • Premiered: 03/28/16
  • Author: Taneja Group
  • Published: Silicon Angle
Topic(s): TBA Galactic Exchange TBA Hadoop TBA hadoop cluster TBA cluster TBA Spark TBA ClusterGX TBA strata TBA simplicity TBA Infrastructure TBA Big Data TBA Mike Matchett TBA Apache TBA Apache Mesos TBA Docker TBA hyperconverged TBA hyperconvergence TBA application performance TBA Backup TBA flexibility TBA Cloud TBA Storage TBA analysis TBA data lake TBA big data lake TBA IoT
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Storage technologies evolve toward a data-processing platform

Emerging technologies such as containers, HCI and big data have blurred the lines between compute and storage platforms, breaking down traditional IT silos.

  • Premiered: 05/18/17
  • Author: Mike Matchett
  • Published: TechTarget: Search Data Center
Topic(s): TBA Storage TBA Big Data TBA Compute TBA HCI TBA hyperconverged TBA hyperconvergence TBA hyperconverged infrastructure TBA container TBA Mike Matchett TBA SDS TBA software-defined TBA software-defined storage TBA Data Storage TBA scale-out TBA Availability TBA convergence TBA HPE TBA SimpliVity TBA Nutanix TBA Hybrid Cloud TBA Cloud TBA server-side flash TBA Flash TBA SSD TBA Datrium TBA DriveScale TBA Igneous TBA Hadoop TBA Spark TBA HDFS
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Secondary data storage: A massively scalable transformation

Capitalize on flash with interactive, online secondary data storage architectures that make a lot more data available for business while maximizing flash investment.

  • Premiered: 10/06/17
  • Author: Mike Matchett
  • Published: TechTarget: Search Storage
Topic(s): TBA secondary data TBA secondary storage TBA Storage TBA scalable TBA scalability TBA SSD TBA Flash TBA Mike Matchett TBA Primary Storage TBA Datacenter TBA Data Center TBA Datrium TBA Big Data TBA Backup TBA Data protection TBA Snapshot TBA Snapshots TBA Archiving TBA Archive TBA Apple TBA second-tier TBA Time Machine TBA convergence TBA Virtualization TBA erasure coding TBA Metadata TBA high availability TBA Capacity TBA Cohesity TBA Hedvig