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By: IBM     Published Date: Jun 05, 2014
In an audited benchmark conducted by STAC®, the Securities Technology Analysis Center, InfoSphere BigInsights for Hadoop was found to deliver an approximate 4x performance gain on average over open source Hadoop running jobs derived from production workload traces. The result is consistent with an approximate eleven times advantage in raw scheduling performance provided by Adaptive MapReduce – a new InfoSphere BigInsights for Hadoop feature that leverages high-performance computing technology from IBM Platform Computing.
Tags : ibm
     IBM
By: IBM     Published Date: Jun 05, 2014
IBM Platform Symphony is a high performance SOA grid server that optimizes application performance and resource sharing. Platform Symphony runs distributed application services on a scalable, shared, heterogeneous grid and accelerates a wide variety of parallel applications, quickly computing results while making optimal use of available infrastructure. Platform Symphony Developer Edition enables developers to rapidly develop and test applications without the need for a production grid. After applications are running in the Developer Edition, they are guaranteed to run at scale once published to a scaled-out Platform Symphony grid. Platform Symphony Developer Edition also enables developers to easily test and verify Hadoop MapReduce applications against IBM Platform Symphony. By leveraging IBM Platform's Symphony's proven, low-latency grid computing solution, more MapReduce jobs can run faster, frequently with less infrastructure.
Tags : ibm
     IBM
By: IBM     Published Date: Jun 05, 2014
In an audited benchmark conducted by STAC®, the Securities Technology Analysis Center, InfoSphere BigInsights for Hadoop was found to deliver an approximate 4x performance gain on average over open source Hadoop running jobs derived from production workload traces. The result is consistent with an approximate eleven times advantage in raw scheduling performance provided by Adaptive MapReduce – a new InfoSphere BigInsights for Hadoop feature that leverages high-performance computing technology from IBM Platform Computing.
Tags : ibm
     IBM
By: IBM     Published Date: Nov 14, 2014
IBM® has created a proprietary implementation of the open-source Hadoop MapReduce run-time that leverages the IBM Platform™ Symphony distributed computing middleware while maintaining application-level compatibility with Apache Hadoop.
Tags : 
     IBM
By: Pentaho     Published Date: Feb 26, 2015
This eBook from O’Reilly Media will help you navigate the diverse and fast-changing landscape of technologies for processing and storing data (NoSQL, big data, MapReduce, etc).
Tags : data systems, data-intensive applications, scalability, maintainability, data storage, application development
     Pentaho
By: Teradata     Published Date: Jan 28, 2015
Althrough Hadoop and related technologies have been with us for several years, most business intelligence (BI) professionals and their business counterparts still harbor a few misconceptions that need to be corrected about Hadoop and related technologies such as MapReduce. This webcast presents the 10 most common myths about Hadoop, then corrects them. The goal is to clarify what Hadoop is and does relative to BI, as well as in which business and technology situations Hadoop-based BI, data warehousing and analytics can be useful.
Tags : teradata, business, intelligence, hadoop, data, integration, analytics, mapreduce, warehouse
     Teradata
By: Teradata     Published Date: Jun 12, 2013
Download this paper to learn how Unified Data Architecture™ can bridge the gap between the business language of SQL, the extreme processing power of MapReduce, and the big data residing in Hadoop to provide a unified, high-performance big data analytics system for the enterprise.
Tags : data, big data, unified data architecture
     Teradata
By: Vertica     Published Date: Oct 30, 2009
Independent research firm Knowledge Integrity Inc. examine two high performance computing technologies that are transitioning into the mainstream: high performance massively parallel analytical database management systems (ADBMS) and distributed parallel programming paradigms, such as MapReduce, (Hadoop, Pig, and HDFS, etc.). By providing an overview of both concepts and looking at how the two approaches can be used together, they conclude that combining a high performance batch programming and execution model with an high performance analytical database provides significant business benefits for a number of different types of applications.
Tags : vertica, analytical computing, adbms, mapreduce, application management, data management, data mining
     Vertica
By: IBM     Published Date: Nov 16, 2015
The report is sponsored by vendor firms Actian Corporation, Cloudera, Exasol, IBM, MapR Technologies, MarkLogic, Pentaho, SAS, Talend, and Trillium Software.
Tags : ibm, tdwi, enterprise, information technology, data management
     IBM
By: Altiscale     Published Date: Aug 25, 2015
Weren't able to attend Hadoop Summit 2015? No sweat. Learn more about the latest Big Data technologies in these technical presentations at this recent leading industry event. The Big Data experts at Altiscale - the leader in Big Data as a Service - have been busy at conferences. To see all four presentations (in slides and youtube video), click here. https://www.altiscale.com/educational-slide-kit-2015-big-data-conferences-nf/ • Managing Growth in Production Hadoop Deployments • Running Spark & MapReduce Together in Production • YARN and the Docker Ecosystem • 5 Tips for Building a Data Science Platform
Tags : hadoop, hadoop technologies, hadoop information
     Altiscale
By: MapR Technologies     Published Date: Dec 12, 2013
Evaluator Group looks at what will make Hadoop an enterprise data center-grade analytics platform.
Tags : big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
     MapR Technologies
By: MapR Technologies     Published Date: Dec 12, 2013
When used effectively, Hadoop can deliver unparalleled value in revealing new analytics-driven revenue streams, improving customer acquisition and retention, as well as increasing operational efficiencies. The Hadoop Buyer's Guide is an invaluable resource for those investigating or evaluating Hadoop---from understanding how Hadoop can solve your data challenges, to what to look for when selecting a solution, to comparing vendors, and preparing for implementation and future success. Download the guide, and get everything you need to know about choosing the right Hadoop distribution for your business success.
Tags : big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
     MapR Technologies
By: MapR Technologies     Published Date: Dec 12, 2013
This independent whitepaper from the Kusnetzky Group Analyst describes the promise and challenges surrounding Big Data. It also validates the M7 solution from MapR, which simplifies big data management by consolidating disparate solutions into a single, enterprise-ready platform.
Tags : big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
     MapR Technologies
By: MapR Technologies     Published Date: Jan 08, 2014
Forrester Research shares seven architectural qualities for evaluating Big Data production platforms. In this webinar guest speaker Mike Gualtieri, Principal Analyst at Forrester, along with experts from MapR and Cisco, will present the following: • The 7 architectural qualities for productionizing Hadoop successfully • Architectural best practices for Big Data applications • The benefits of planning for scale • How Cisco IT is using best practices for their Big Data applications Speakers • Mike Gualtieri, Principal Analyst at Forrester Research • Jack Norris, Chief Marketing Officer at MapR Technologies • Andrew Blaisdell, Product Marketing Manager at Cisco • Sudharshan Seerapu, IT Engineer at Cisco
Tags : big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
     MapR Technologies
By: MapR Technologies     Published Date: Jan 03, 2014
As the demand for Big Data analytics mushrooms, IT decision-makers must prepare for the widespread deployment of Hadoop. This Technical Insight Paper from the Evaluator Group outlines the key requirements that must be met to make Hadoop enterprise data center ready.
Tags : big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
     MapR Technologies
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