Supercomputing and Big Data: Where are the Real Boundaries and Opportunities for Synergy?
|
|
- Tracy Joseph
- 8 years ago
- Views:
Transcription
1 HPC2012 Workshop Cetraro, Italy Supercomputing and Big Data: Where are the Real Boundaries and Opportunities for Synergy? Bill Blake CTO Cray, Inc.
2 The Big Data Challenge Supercomputing minimizes data movement The focus is loading the mesh in distributed memory, computing the answer with fast interconnects, and visualizing the answer in memory the high performance data movement is for loading, check pointing or archiving. Data-intensive computing is all about data movement The focus is scanning, sorting, streaming and aggregating "all the data all the time" to get the answer or discover new knowledge from unstructured/structured data sources. 6/30/2012 2
3 Big Data is Data in Motion Set the stage for the fusion of numerically intensive and data intensive computing in future Cray systems Build on Cray's success of delivering the most scalable systems through heterogeneous and specialized nodes Nodes not only optimized for compute, but also storage and network I/O, all connected with the highest level of interconnect performance. Add system capability to the edge of the fabric We see this effort as increasing key application performance with an "appliance style" approach using Cray's primary supercomputing products with extensions configured as optimized HW/SW stacks adding value around the edge of the high performance system network 6/30/2012 3
4 Maximum Scalability: System Node Specialization Key to Cray s MPP scalability is system node o/s specialization combined with very high bandwidth, low latency interconnects A very effective approach to appliance design: Netezza and Cray examples Service Compute File I/O Price Enterprise servers 100,000s units High-Performance Computing 1,000s units /home Users Net I/O PCs and Workstations 10,000,000s units System Support Sys Admin Performance Courtesy of Dr. Bill Camp, Sandia National Laboratories, circa 2000
5 Back in Time, at the Beginnings of the Web, there was Dr. Codd and his Relational Database Algebraic Set Theory
6 Analyzing Big Data Analytics: A Swim Lane View of Supporting Business and Technical Decisions Key Function Language Data Approach Airline Example OLTP Declarative (SQL) Structured (relational) ATM transactions Buying a seat on an airplane OLAP Ad Hoc Declarative (SQL+UDF) Structured (relational) BI aggregate and analyze bookings for new ad placements Semantic Ad hoc Declarative (SPARQL) Linked, Open (graph-based) Analyze social graphs and infer who might travel where OLAP Ad Hoc Procedural (MapReduce) Unstructured (Hadoop files) Application Framework for weblog analysis Optimize Models Procedural (Solver Libs) Optimization <-> Simulation Complex Scheduling Estimating empty seats Simulate Models Procedural (Fortran, C++) Matrix Math (Systems of Eq s) Mathematical Modeling and simulation (design airplane)
7 For Perspective (1980 s) Key Function Language Data Approach SMP Server Cluster And MPP Cloud And Grid Web Scale OLTP Declarative (SQL) Structured (relational) The relational database was invented on a system that merged server, storage and database CPU Memory It was called a mainframe IOP IOP Change focus to vector processing and memory performance and the mainframe becomes a supercomputer
8 Processing millions of transactions without a hitch Do entire transaction or nothing (don t debit account without dispensing cash) Disciplined approach to data forms data models/schema tables on disk Tables at first glance look like the rows and columns of a spreadsheet Transaction processing uses highly repetitive queries for entering/updating OLTP: Processing Tables with Queries Key Function OLTP Language Declarative (SQL) Data Approach Structured (relational) SMP Server Cluster And MPP Cloud And Grid Web Scale
9 OLTP: Processing Tables with Queries A transaction touches only the data it needs to accomplish its purpose Since the workload involves many, many small data payloads, speedups can be gained through caching and the use of indices that prevent full table scans. The query states what it needs, and the database uses a (cost-based) planner/optimizer to create the program that actually manipulates the tables Mostly writing to the database
10 Then The Rules Changed Mainframes attacked by killer micros! Memory grew large I/O became weak System costs dropped Storage moved off to the network CPU CPU CPU CPU CPU CPU CPU CPU Very Large Memory I/O Storage Area Network
11 Capacity Was Added By Clustering CPU CPU CPU CPU CPU CPU CPU CPU CPU CPU CPU CPU Memory I/O Memory I/O I/O Memory I/O I/O Storage Area Network Memory Memory CPU CPU CPU CPU CPU CPU CPU CPU SAN limits Moving Data to the Processors
12 The Online Analytical Processing Problem Key Function Language Data Approach SMP Server Cluster And MPP Cloud And Grid Web Scale OLAP Ad Hoc Declarative (SQL+UDF ) Structured (relational) Business Intelligence Applications generate reports of aggregations Need to read at all the data all the time (telecom, retail, finance, advertising, etc) BI Analytics require ad hoc queries since you don t know the next question to ask until you understand the answer to the last question Standard SQL is limited by the Algebraic Set Theory basis of RDBMS, if you need Calculus then insert User Defined Functions into the SQL Programming models in conflict as Modeling and Simulation combine with Business Intelligence in Predictive Analytics
13 Operational vs. Analytical RDBMS Extraction /Cleansing Transformation Loading Reports OLTP Databases Processing Millions Of Transactions/sec OLAP Databases aka Data Warehouse Processing Hundreds of Terabytes/hour
14 Data Flow The SAN Bottleneck Applications Client $$$ Processing $$$ Fiber Channels $$$ Storage SMP HOST 1 $$$ C6 C12 F7 F13 C38 F39 G13 G22 SMP HOST 2 $$$ SMP HOST N Local Applications Hours or Days
15 The Netezza Idea: Moving Processing to the Data Active Disk architectures Integrated processing power and memory into disk units Scaled processing power as the dataset grew Decision support algorithms offloaded to Active Disks to support key decision support tasks Active Disk architectures use stream-based model ideal for the software architecture of relational databases Influenced by the success of Cisco and NetApp appliances, the approach combined software, processing, networking and storage leading to the first database warehouse appliance! Netezza is an IBM Company
16 The HW Architecture Responded to the Needs of the Database Application BI Applications Client ODBC 3.X JDBC Type 4 SQL/92 Netezza Performance Server Front End SQL Compiler Query Plan Optimize Admin The Database Application Execution Engine DBOS Gigabit Ethernet Snippet Processing Unit (SPU) Processor + streaming DB logic Processor + streaming DB logic Processor + streaming DB logic High-Performance Database Engine Streaming joins, aggregations, sorts, etc. Local Applications Fast Loader/Unloader Linux SMP Host Processor + streaming DB logic Massively Parallel Intelligent Storage Move processing to the data (maximum I/O to a single table)
17 Shifting from Analyst to Programmer Key Function Language Data Approach SMP Server Cluster And MPP Cloud And Grid Web Scale OLAP Ad Hoc Procedural (MapReduce) Unstructured (Hadoop Files) Google, Yahoo and their friends are using a data-intensive application framework to analyze very large datasets (e.g.,weblogs) without transactions or structured data What will this look like in 10 years? MapReduce/Hadoop: an programming model/application framework performing group-by (map), sort and aggregation (reduce) Not queries, but programs willing to forgo the need for transactional integrity or the performance of structured data (4X-5X disadvantage on equal hardware, but with excellent scaling on cheap hardware) An increasingly popular approach with organizations that have the programming talent to use it, especially research organizations Another frontal assault on the $40K per socket RDBMS licensing
18 Analysis is Getting Complex Multi-dimensional predictive queries Connection networks, social network, Time, Space, Reasoning Find why the customers who live on the 25 th street in Zurich did not switch their phone company between March 23 to August 19 while their friends and family switched their phone company and predict the trend moving forward? Need to pick weak signals from the noise Data size will continue to grow and be more heterogeneous Finding needle in a hay stack will become more important Will require real time or shorter turnaround time Differentiation will be based on the speed of analysis of changing data INFERENCE maybe as a legitimate answer 18
19 Advancing from Generating Reports to Inference and Discovery Key Function Language Data Approach SMP Server Cluster And MPP Cloud And Grid Web Scale Semantic Ad hoc Declarative (SPARQL) Linked, Open (graph-based) The International W3C standards body has approved the key standards, called RDF and OWL to support the Semantic Web aka Web 3.0 with machine readable open linked data Future databases will use triples (subject-predicate-object) vs tables and with RDF/OWL federate heterogeneous data Future databases will support reasoning not just reporting This work started as a combined European Defense and DARPA effort Major RDBMS vendors are admitting Relational and XML are ill-suited to the needs of the semantic web of the future
20 The Idea: Address Memory and Network Latency Decision support algorithms offloaded to multithreaded processors and in-memory database with new complex key decision support tasks Supports new SPARQL query processing for RDF triples database offering the speedup of XMT processing without low level API Shared memory, multi-threaded Cray technology Integrated with semantic database (open source std compliant) Fastest complex query response on open linked data in the industry Influenced by the success of database warehouse appliances, our combined (database) software, processing, networking and memory led to the first graph appliance! Deliver easy to deploy solutions requiring knowledge discovery for Intelligence, Bioinformatics, Finance, etc.
21 Now a new tool for data analysis. Performs like a supercomputer Uses open web 3.0 standards? Operates like a data warehouse Scales like a web engine 21
22 Adapt the system to the application not the application to the systemvision: Exascale Cray s Adaptive Supercomputing combines multiple processing architectures into a single scalable system CPU, GPU, or Multithreaded The focus in on the user s application where the adaptive software, the compiler or query processor, knows what types of processors are available on the heterogeneous system and targets code to the most appropriate processor The next step is to evolve Adaptive Supercomputing to Big Data workloads
23 Enabling Simulation and Data Science Adaptive Supercomputing
24
HPC and Large Scale Data Analytics. SOS17 Conference Jekyll Island, Georgia
HPC and Large Scale Data Analytics SOS17 Conference Jekyll Island, Georgia Bill Blake CTO Cray Inc March 26, 2013 HPC and Large-scale Data Analytics Divergence or Convergence? Supercomputing Highest performance
More informationA Data Warehouse Approach to Analyzing All the Data All the Time. Bill Blake Netezza Corporation April 2006
A Data Warehouse Approach to Analyzing All the Data All the Time Bill Blake Netezza Corporation April 2006 Sometimes A Different Approach Is Useful The challenge of scaling up systems where many applications
More informationCray: Enabling Real-Time Discovery in Big Data
Cray: Enabling Real-Time Discovery in Big Data Discovery is the process of gaining valuable insights into the world around us by recognizing previously unknown relationships between occurrences, objects
More informationOracle BI EE Implementation on Netezza. Prepared by SureShot Strategies, Inc.
Oracle BI EE Implementation on Netezza Prepared by SureShot Strategies, Inc. The goal of this paper is to give an insight to Netezza architecture and implementation experience to strategize Oracle BI EE
More informationThe Fusion of Supercomputing and Big Data: The Role of Global Memory Architectures in Future Large Scale Data Analytics
HPC 2014 High Performance Computing FROM clouds and BIG DATA to EXASCALE AND BEYOND An International Advanced Workshop July 7 11, 2014, Cetraro, Italy Session III Emerging Systems and Solutions The Fusion
More informationIBM Netezza High Capacity Appliance
IBM Netezza High Capacity Appliance Petascale Data Archival, Analysis and Disaster Recovery Solutions IBM Netezza High Capacity Appliance Highlights: Allows querying and analysis of deep archival data
More informationWell packaged sets of preinstalled, integrated, and optimized software on select hardware in the form of engineered systems and appliances
INSIGHT Oracle's All- Out Assault on the Big Data Market: Offering Hadoop, R, Cubes, and Scalable IMDB in Familiar Packages Carl W. Olofson IDC OPINION Global Headquarters: 5 Speen Street Framingham, MA
More informationManaging Big Data with Hadoop & Vertica. A look at integration between the Cloudera distribution for Hadoop and the Vertica Analytic Database
Managing Big Data with Hadoop & Vertica A look at integration between the Cloudera distribution for Hadoop and the Vertica Analytic Database Copyright Vertica Systems, Inc. October 2009 Cloudera and Vertica
More informationComplexity and Scalability in Semantic Graph Analysis Semantic Days 2013
Complexity and Scalability in Semantic Graph Analysis Semantic Days 2013 James Maltby, Ph.D 1 Outline of Presentation Semantic Graph Analytics Database Architectures In-memory Semantic Database Formulation
More informationNetezza and Business Analytics Synergy
Netezza Business Partner Update: November 17, 2011 Netezza and Business Analytics Synergy Shimon Nir, IBM Agenda Business Analytics / Netezza Synergy Overview Netezza overview Enabling the Business with
More informationBIG DATA IN THE CLOUD : CHALLENGES AND OPPORTUNITIES MARY- JANE SULE & PROF. MAOZHEN LI BRUNEL UNIVERSITY, LONDON
BIG DATA IN THE CLOUD : CHALLENGES AND OPPORTUNITIES MARY- JANE SULE & PROF. MAOZHEN LI BRUNEL UNIVERSITY, LONDON Overview * Introduction * Multiple faces of Big Data * Challenges of Big Data * Cloud Computing
More informationBig Data Technologies Compared June 2014
Big Data Technologies Compared June 2014 Agenda What is Big Data Big Data Technology Comparison Summary Other Big Data Technologies Questions 2 What is Big Data by Example The SKA Telescope is a new development
More informationThe Fusion of Supercomputing and Big Data. Peter Ungaro President & CEO
The Fusion of Supercomputing and Big Data Peter Ungaro President & CEO The Supercomputing Company Supercomputing Big Data Because some great things never change One other thing that hasn t changed. Cray
More informationThe Evolution of Microsoft SQL Server: The right time for Violin flash Memory Arrays
The Evolution of Microsoft SQL Server: The right time for Violin flash Memory Arrays Executive Summary Microsoft SQL has evolved beyond serving simple workgroups to a platform delivering sophisticated
More informationIBM Data Retrieval Technologies: RDBMS, BLU, IBM Netezza, and Hadoop
IBM Data Retrieval Technologies: RDBMS, BLU, IBM Netezza, and Hadoop Frank C. Fillmore, Jr. The Fillmore Group, Inc. Session Code: E13 Wed, May 06, 2015 (02:15 PM - 03:15 PM) Platform: Cross-platform Objectives
More informationCost-Effective Business Intelligence with Red Hat and Open Source
Cost-Effective Business Intelligence with Red Hat and Open Source Sherman Wood Director, Business Intelligence, Jaspersoft September 3, 2009 1 Agenda Introductions Quick survey What is BI?: reporting,
More informationESS event: Big Data in Official Statistics. Antonino Virgillito, Istat
ESS event: Big Data in Official Statistics Antonino Virgillito, Istat v erbi v is 1 About me Head of Unit Web and BI Technologies, IT Directorate of Istat Project manager and technical coordinator of Web
More informationA REVIEW PAPER ON THE HADOOP DISTRIBUTED FILE SYSTEM
A REVIEW PAPER ON THE HADOOP DISTRIBUTED FILE SYSTEM Sneha D.Borkar 1, Prof.Chaitali S.Surtakar 2 Student of B.E., Information Technology, J.D.I.E.T, sborkar95@gmail.com Assistant Professor, Information
More informationIBM PureData Systems. Robert Božič robert.bozic@si.ibm.com. 2013 IBM Corporation
IBM PureData Systems Robert Božič robert.bozic@si.ibm.com IBM PureData System Meeting Big Data Challenges Fast and Easy! System for Hadoop For Exploratory Analysis & Queryable Archive Hadoop data services
More informationbigdata Managing Scale in Ontological Systems
Managing Scale in Ontological Systems 1 This presentation offers a brief look scale in ontological (semantic) systems, tradeoffs in expressivity and data scale, and both information and systems architectural
More informationCisco UCS and Fusion- io take Big Data workloads to extreme performance in a small footprint: A case study with Oracle NoSQL database
Cisco UCS and Fusion- io take Big Data workloads to extreme performance in a small footprint: A case study with Oracle NoSQL database Built up on Cisco s big data common platform architecture (CPA), a
More informationPractical Approaches to Big Data & Analytics: From Infrastructure to
2014 Cisco and/or its affiliates. All rights reserved. Practical Approaches to Big Data & Analytics: From Infrastructure to Applications Kapil Bakshi Distinguished Architect, Cisco System Digital Government
More informationHow To Handle Big Data With A Data Scientist
III Big Data Technologies Today, new technologies make it possible to realize value from Big Data. Big data technologies can replace highly customized, expensive legacy systems with a standard solution
More informationQLIKVIEW INTEGRATION TION WITH AMAZON REDSHIFT John Park Partner Engineering
QLIKVIEW INTEGRATION TION WITH AMAZON REDSHIFT John Park Partner Engineering June 2014 Page 1 Contents Introduction... 3 About Amazon Web Services (AWS)... 3 About Amazon Redshift... 3 QlikView on AWS...
More informationArchitectures for Big Data Analytics A database perspective
Architectures for Big Data Analytics A database perspective Fernando Velez Director of Product Management Enterprise Information Management, SAP June 2013 Outline Big Data Analytics Requirements Spectrum
More informationOverview: X5 Generation Database Machines
Overview: X5 Generation Database Machines Spend Less by Doing More Spend Less by Paying Less Rob Kolb Exadata X5-2 Exadata X4-8 SuperCluster T5-8 SuperCluster M6-32 Big Memory Machine Oracle Exadata Database
More informationUbrzajte svoj Data Warehouse 100 puta i više
Ubrzajte svoj Data Warehouse 100 puta i više Robert Božič robert.bozic@si.ibm.com 2012 IBM Corporation Agenda Primjer razvoja Data Warehouse okoline u Zavarovalnici Maribor Kako može IBM pomoči kod ubrzanja
More informationInge Os Sales Consulting Manager Oracle Norway
Inge Os Sales Consulting Manager Oracle Norway Agenda Oracle Fusion Middelware Oracle Database 11GR2 Oracle Database Machine Oracle & Sun Agenda Oracle Fusion Middelware Oracle Database 11GR2 Oracle Database
More informationScaling Your Data to the Cloud
ZBDB Scaling Your Data to the Cloud Technical Overview White Paper POWERED BY Overview ZBDB Zettabyte Database is a new, fully managed data warehouse on the cloud, from SQream Technologies. By building
More informationSo#ware Tools and Techniques for HPC, Clouds, and Server- Class SoCs Ron Brightwell
So#ware Tools and Techniques for HPC, Clouds, and Server- Class SoCs Ron Brightwell R&D Manager, Scalable System So#ware Department Sandia National Laboratories is a multi-program laboratory managed and
More informationW H I T E P A P E R. Deriving Intelligence from Large Data Using Hadoop and Applying Analytics. Abstract
W H I T E P A P E R Deriving Intelligence from Large Data Using Hadoop and Applying Analytics Abstract This white paper is focused on discussing the challenges facing large scale data processing and the
More informationInformation Architecture
The Bloor Group Actian and The Big Data Information Architecture WHITE PAPER The Actian Big Data Information Architecture Actian and The Big Data Information Architecture Originally founded in 2005 to
More informationNoSQL for SQL Professionals William McKnight
NoSQL for SQL Professionals William McKnight Session Code BD03 About your Speaker, William McKnight President, McKnight Consulting Group Frequent keynote speaker and trainer internationally Consulted to
More informationHadoop. http://hadoop.apache.org/ Sunday, November 25, 12
Hadoop http://hadoop.apache.org/ What Is Apache Hadoop? The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using
More informationAffordable, Scalable, Reliable OLTP in a Cloud and Big Data World: IBM DB2 purescale
WHITE PAPER Affordable, Scalable, Reliable OLTP in a Cloud and Big Data World: IBM DB2 purescale Sponsored by: IBM Carl W. Olofson December 2014 IN THIS WHITE PAPER This white paper discusses the concept
More informationNext-Generation Cloud Analytics with Amazon Redshift
Next-Generation Cloud Analytics with Amazon Redshift What s inside Introduction Why Amazon Redshift is Great for Analytics Cloud Data Warehousing Strategies for Relational Databases Analyzing Fast, Transactional
More informationHigh Performance Computing. Course Notes 2007-2008. HPC Fundamentals
High Performance Computing Course Notes 2007-2008 2008 HPC Fundamentals Introduction What is High Performance Computing (HPC)? Difficult to define - it s a moving target. Later 1980s, a supercomputer performs
More informationOracle s Big Data solutions. Roger Wullschleger. <Insert Picture Here>
s Big Data solutions Roger Wullschleger DBTA Workshop on Big Data, Cloud Data Management and NoSQL 10. October 2012, Stade de Suisse, Berne 1 The following is intended to outline
More informationBig Data Analytics - Accelerated. stream-horizon.com
Big Data Analytics - Accelerated stream-horizon.com Legacy ETL platforms & conventional Data Integration approach Unable to meet latency & data throughput demands of Big Data integration challenges Based
More informationPreview of Oracle Database 12c In-Memory Option. Copyright 2013, Oracle and/or its affiliates. All rights reserved.
Preview of Oracle Database 12c In-Memory Option 1 The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any
More informationANALYTICS IN BIG DATA ERA
ANALYTICS IN BIG DATA ERA ANALYTICS TECHNOLOGY AND ARCHITECTURE TO MANAGE VELOCITY AND VARIETY, DISCOVER RELATIONSHIPS AND CLASSIFY HUGE AMOUNT OF DATA MAURIZIO SALUSTI SAS Copyr i g ht 2012, SAS Ins titut
More informationNextGen Infrastructure for Big DATA Analytics.
NextGen Infrastructure for Big DATA Analytics. So What is Big Data? Data that exceeds the processing capacity of conven4onal database systems. The data is too big, moves too fast, or doesn t fit the structures
More informationAgenda. HPC Software Stack. HPC Post-Processing Visualization. Case Study National Scientific Center. European HPC Benchmark Center Montpellier PSSC
HPC Architecture End to End Alexandre Chauvin Agenda HPC Software Stack Visualization National Scientific Center 2 Agenda HPC Software Stack Alexandre Chauvin Typical HPC Software Stack Externes LAN Typical
More informationUnderstanding the Value of In-Memory in the IT Landscape
February 2012 Understing the Value of In-Memory in Sponsored by QlikView Contents The Many Faces of In-Memory 1 The Meaning of In-Memory 2 The Data Analysis Value Chain Your Goals 3 Mapping Vendors to
More information4 th Workshop on Big Data Benchmarking
4 th Workshop on Big Data Benchmarking MPP SQL Engines: architectural choices and their implications on benchmarking 09 Oct 2013 Agenda: Big Data Landscape Market Requirements Benchmark Parameters Benchmark
More informationBig Data Processing: Past, Present and Future
Big Data Processing: Past, Present and Future Orion Gebremedhin National Solutions Director BI & Big Data, Neudesic LLC. VTSP Microsoft Corp. Orion.Gebremedhin@Neudesic.COM B-orgebr@Microsoft.com @OrionGM
More informationSAS and Oracle: Big Data and Cloud Partnering Innovation Targets the Third Platform
SAS and Oracle: Big Data and Cloud Partnering Innovation Targets the Third Platform David Lawler, Oracle Senior Vice President, Product Management and Strategy Paul Kent, SAS Vice President, Big Data What
More informationTHE DEVELOPER GUIDE TO BUILDING STREAMING DATA APPLICATIONS
THE DEVELOPER GUIDE TO BUILDING STREAMING DATA APPLICATIONS WHITE PAPER Successfully writing Fast Data applications to manage data generated from mobile, smart devices and social interactions, and the
More informationParallel Computing. Benson Muite. benson.muite@ut.ee http://math.ut.ee/ benson. https://courses.cs.ut.ee/2014/paralleel/fall/main/homepage
Parallel Computing Benson Muite benson.muite@ut.ee http://math.ut.ee/ benson https://courses.cs.ut.ee/2014/paralleel/fall/main/homepage 3 November 2014 Hadoop, Review Hadoop Hadoop History Hadoop Framework
More informationChukwa, Hadoop subproject, 37, 131 Cloud enabled big data, 4 Codd s 12 rules, 1 Column-oriented databases, 18, 52 Compression pattern, 83 84
Index A Amazon Web Services (AWS), 50, 58 Analytics engine, 21 22 Apache Kafka, 38, 131 Apache S4, 38, 131 Apache Sqoop, 37, 131 Appliance pattern, 104 105 Application architecture, big data analytics
More informationEinsatzfelder von IBM PureData Systems und Ihre Vorteile.
Einsatzfelder von IBM PureData Systems und Ihre Vorteile demirkaya@de.ibm.com Agenda Information technology challenges PureSystems and PureData introduction PureData for Transactions PureData for Analytics
More informationHP Oracle Database Platform / Exadata Appliance Extreme Data Warehousing
HP Oracle Database Platform / Exadata Appliance Extreme Data Warehousing Shyam Varan Nath President, Oracle BIWA SIG & Founder Exadata SIG (http://oracleexadata.org) South Florida Oracle User Group March
More informationAchieving Real-Time Business Solutions Using Graph Database Technology and High Performance Networks
WHITE PAPER July 2014 Achieving Real-Time Business Solutions Using Graph Database Technology and High Performance Networks Contents Executive Summary...2 Background...3 InfiniteGraph...3 High Performance
More informationInfrastructure Matters: POWER8 vs. Xeon x86
Advisory Infrastructure Matters: POWER8 vs. Xeon x86 Executive Summary This report compares IBM s new POWER8-based scale-out Power System to Intel E5 v2 x86- based scale-out systems. A follow-on report
More informationEmerging Technologies Shaping the Future of Data Warehouses & Business Intelligence
Emerging Technologies Shaping the Future of Data Warehouses & Business Intelligence Appliances and DW Architectures John O Brien President and Executive Architect Zukeran Technologies 1 TDWI 1 Agenda What
More informationData-intensive HPC: opportunities and challenges. Patrick Valduriez
Data-intensive HPC: opportunities and challenges Patrick Valduriez Big Data Landscape Multi-$billion market! Big data = Hadoop = MapReduce? No one-size-fits-all solution: SQL, NoSQL, MapReduce, No standard,
More informationPARALLEL & CLUSTER COMPUTING CS 6260 PROFESSOR: ELISE DE DONCKER BY: LINA HUSSEIN
1 PARALLEL & CLUSTER COMPUTING CS 6260 PROFESSOR: ELISE DE DONCKER BY: LINA HUSSEIN Introduction What is cluster computing? Classification of Cluster Computing Technologies: Beowulf cluster Construction
More informationNews and trends in Data Warehouse Automation, Big Data and BI. Johan Hendrickx & Dirk Vermeiren
News and trends in Data Warehouse Automation, Big Data and BI Johan Hendrickx & Dirk Vermeiren Extreme Agility from Source to Analysis DWH Appliances & DWH Automation Typical Architecture 3 What Business
More informationOracle Big Data SQL Technical Update
Oracle Big Data SQL Technical Update Jean-Pierre Dijcks Oracle Redwood City, CA, USA Keywords: Big Data, Hadoop, NoSQL Databases, Relational Databases, SQL, Security, Performance Introduction This technical
More informationCluster, Grid, Cloud Concepts
Cluster, Grid, Cloud Concepts Kalaiselvan.K Contents Section 1: Cluster Section 2: Grid Section 3: Cloud Cluster An Overview Need for a Cluster Cluster categorizations A computer cluster is a group of
More informationMain Memory Data Warehouses
Main Memory Data Warehouses Robert Wrembel Poznan University of Technology Institute of Computing Science Robert.Wrembel@cs.put.poznan.pl www.cs.put.poznan.pl/rwrembel Lecture outline Teradata Data Warehouse
More informationInnovative technology for big data analytics
Technical white paper Innovative technology for big data analytics The HP Vertica Analytics Platform database provides price/performance, scalability, availability, and ease of administration Table of
More informationExecutive Summary... 2 Introduction... 3. Defining Big Data... 3. The Importance of Big Data... 4 Building a Big Data Platform...
Executive Summary... 2 Introduction... 3 Defining Big Data... 3 The Importance of Big Data... 4 Building a Big Data Platform... 5 Infrastructure Requirements... 5 Solution Spectrum... 6 Oracle s Big Data
More informationI/O Considerations in Big Data Analytics
Library of Congress I/O Considerations in Big Data Analytics 26 September 2011 Marshall Presser Federal Field CTO EMC, Data Computing Division 1 Paradigms in Big Data Structured (relational) data Very
More informationIntroducing Oracle Exalytics In-Memory Machine
Introducing Oracle Exalytics In-Memory Machine Jon Ainsworth Director of Business Development Oracle EMEA Business Analytics 1 Copyright 2011, Oracle and/or its affiliates. All rights Agenda Topics Oracle
More information2009 Oracle Corporation 1
The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material,
More informationScaling Objectivity Database Performance with Panasas Scale-Out NAS Storage
White Paper Scaling Objectivity Database Performance with Panasas Scale-Out NAS Storage A Benchmark Report August 211 Background Objectivity/DB uses a powerful distributed processing architecture to manage
More informationIncreasing Flash Throughput for Big Data Applications (Data Management Track)
Scale Simplify Optimize Evolve Increasing Flash Throughput for Big Data Applications (Data Management Track) Flash Memory 1 Industry Context Addressing the challenge A proposed solution Review of the Benefits
More informationNext Generation Data Warehousing Appliances 23.10.2014
Next Generation Data Warehousing Appliances 23.10.2014 Presentert av: Espen Jorde, Executive Advisor Bjørn Runar Nes, CTO/Chief Architect Bjørn Runar Nes Espen Jorde 2 3.12.2014 Agenda Affecto s new Data
More informationEvaluating NoSQL for Enterprise Applications. Dirk Bartels VP Strategy & Marketing
Evaluating NoSQL for Enterprise Applications Dirk Bartels VP Strategy & Marketing Agenda The Real Time Enterprise The Data Gold Rush Managing The Data Tsunami Analytics and Data Case Studies Where to go
More informationParallel Data Warehouse
MICROSOFT S ANALYTICS SOLUTIONS WITH PARALLEL DATA WAREHOUSE Parallel Data Warehouse Stefan Cronjaeger Microsoft May 2013 AGENDA PDW overview Columnstore and Big Data Business Intellignece Project Ability
More informationBig Data & QlikView. Democratizing Big Data Analytics. David Freriks Principal Solution Architect
Big Data & QlikView Democratizing Big Data Analytics David Freriks Principal Solution Architect TDWI Vancouver Agenda What really is Big Data? How do we separate hype from reality? How does that relate
More informationOracle Database 11g Comparison Chart
Key Feature Summary Express 10g Standard One Standard Enterprise Maximum 1 CPU 2 Sockets 4 Sockets No Limit RAM 1GB OS Max OS Max OS Max Database Size 4GB No Limit No Limit No Limit Windows Linux Unix
More informationSAP HANA SAP s In-Memory Database. Dr. Martin Kittel, SAP HANA Development January 16, 2013
SAP HANA SAP s In-Memory Database Dr. Martin Kittel, SAP HANA Development January 16, 2013 Disclaimer This presentation outlines our general product direction and should not be relied on in making a purchase
More informationHigh Performance Computing in CST STUDIO SUITE
High Performance Computing in CST STUDIO SUITE Felix Wolfheimer GPU Computing Performance Speedup 18 16 14 12 10 8 6 4 2 0 Promo offer for EUC participants: 25% discount for K40 cards Speedup of Solver
More informationFIFTH EDITION. Oracle Essentials. Rick Greenwald, Robert Stackowiak, and. Jonathan Stern O'REILLY" Tokyo. Koln Sebastopol. Cambridge Farnham.
FIFTH EDITION Oracle Essentials Rick Greenwald, Robert Stackowiak, and Jonathan Stern O'REILLY" Beijing Cambridge Farnham Koln Sebastopol Tokyo _ Table of Contents Preface xiii 1. Introducing Oracle 1
More informationCluster Implementation and Management; Scheduling
Cluster Implementation and Management; Scheduling CPS343 Parallel and High Performance Computing Spring 2013 CPS343 (Parallel and HPC) Cluster Implementation and Management; Scheduling Spring 2013 1 /
More informationBig Fast Data Hadoop acceleration with Flash. June 2013
Big Fast Data Hadoop acceleration with Flash June 2013 Agenda The Big Data Problem What is Hadoop Hadoop and Flash The Nytro Solution Test Results The Big Data Problem Big Data Output Facebook Traditional
More informationCloud Computing and Advanced Relationship Analytics
Cloud Computing and Advanced Relationship Analytics Using Objectivity/DB to Discover the Relationships in your Data By Brian Clark Vice President, Product Management Objectivity, Inc. 408 992 7136 brian.clark@objectivity.com
More informationHadoop and Relational Database The Best of Both Worlds for Analytics Greg Battas Hewlett Packard
Hadoop and Relational base The Best of Both Worlds for Analytics Greg Battas Hewlett Packard The Evolution of Analytics Mainframe EDW Proprietary MPP Unix SMP MPP Appliance Hadoop? Questions Is Hadoop
More informationRackspace Cloud Databases and Container-based Virtualization
Rackspace Cloud Databases and Container-based Virtualization August 2012 J.R. Arredondo @jrarredondo Page 1 of 6 INTRODUCTION When Rackspace set out to build the Cloud Databases product, we asked many
More informationIBM AND NEXT GENERATION ARCHITECTURE FOR BIG DATA & ANALYTICS!
The Bloor Group IBM AND NEXT GENERATION ARCHITECTURE FOR BIG DATA & ANALYTICS VENDOR PROFILE The IBM Big Data Landscape IBM can legitimately claim to have been involved in Big Data and to have a much broader
More informationBIG DATA TRENDS AND TECHNOLOGIES
BIG DATA TRENDS AND TECHNOLOGIES THE WORLD OF DATA IS CHANGING Cloud WHAT IS BIG DATA? Big data are datasets that grow so large that they become awkward to work with using onhand database management tools.
More informationArchitectural patterns for building real time applications with Apache HBase. Andrew Purtell Committer and PMC, Apache HBase
Architectural patterns for building real time applications with Apache HBase Andrew Purtell Committer and PMC, Apache HBase Who am I? Distributed systems engineer Principal Architect in the Big Data Platform
More informationBringing Big Data into the Enterprise
Bringing Big Data into the Enterprise Overview When evaluating Big Data applications in enterprise computing, one often-asked question is how does Big Data compare to the Enterprise Data Warehouse (EDW)?
More informationEnd to End Solution to Accelerate Data Warehouse Optimization. Franco Flore Alliance Sales Director - APJ
End to End Solution to Accelerate Data Warehouse Optimization Franco Flore Alliance Sales Director - APJ Big Data Is Driving Key Business Initiatives Increase profitability, innovation, customer satisfaction,
More informationBig Data and Your Data Warehouse Philip Russom
Big Data and Your Data Warehouse Philip Russom TDWI Research Director for Data Management April 5, 2012 Sponsor Speakers Philip Russom Research Director, Data Management, TDWI Peter Jeffcock Director,
More informationJames Serra Sr BI Architect JamesSerra3@gmail.com http://jamesserra.com/
James Serra Sr BI Architect JamesSerra3@gmail.com http://jamesserra.com/ Our Focus: Microsoft Pure-Play Data Warehousing & Business Intelligence Partner Our Customers: Our Reputation: "B.I. Voyage came
More informationHigh Availability Databases based on Oracle 10g RAC on Linux
High Availability Databases based on Oracle 10g RAC on Linux WLCG Tier2 Tutorials, CERN, June 2006 Luca Canali, CERN IT Outline Goals Architecture of an HA DB Service Deployment at the CERN Physics Database
More informationDecoding the Big Data Deluge a Virtual Approach. Dan Luongo, Global Lead, Field Solution Engineering Data Virtualization Business Unit, Cisco
Decoding the Big Data Deluge a Virtual Approach Dan Luongo, Global Lead, Field Solution Engineering Data Virtualization Business Unit, Cisco High-volume, velocity and variety information assets that demand
More informationYarcData urika Technical White Paper
YarcData urika Technical White Paper 2012 Cray Inc. All rights reserved. Specifications subject to change without notice. Cray is a registered trademark, YarcData, urika and Threadstorm are trademarks
More informationUsing Tableau Software with Hortonworks Data Platform
Using Tableau Software with Hortonworks Data Platform September 2013 2013 Hortonworks Inc. http:// Modern businesses need to manage vast amounts of data, and in many cases they have accumulated this data
More informationApache Hadoop in the Enterprise. Dr. Amr Awadallah, CTO/Founder @awadallah, aaa@cloudera.com
Apache Hadoop in the Enterprise Dr. Amr Awadallah, CTO/Founder @awadallah, aaa@cloudera.com Cloudera The Leader in Big Data Management Powered by Apache Hadoop The Leading Open Source Distribution of Apache
More informationBig Data Challenges in Bioinformatics
Big Data Challenges in Bioinformatics BARCELONA SUPERCOMPUTING CENTER COMPUTER SCIENCE DEPARTMENT Autonomic Systems and ebusiness Pla?orms Jordi Torres Jordi.Torres@bsc.es Talk outline! We talk about Petabyte?
More informationBig Data Technology ดร.ช ชาต หฤไชยะศ กด. Choochart Haruechaiyasak, Ph.D.
Big Data Technology ดร.ช ชาต หฤไชยะศ กด Choochart Haruechaiyasak, Ph.D. Speech and Audio Technology Laboratory (SPT) National Electronics and Computer Technology Center (NECTEC) National Science and Technology
More informationPerformance and Scalability Overview
Performance and Scalability Overview This guide provides an overview of some of the performance and scalability capabilities of the Pentaho Business Analytics Platform. Contents Pentaho Scalability and
More informationIn-memory computing with SAP HANA
In-memory computing with SAP HANA June 2015 Amit Satoor, SAP @asatoor 2015 SAP SE or an SAP affiliate company. All rights reserved. 1 Hyperconnectivity across people, business, and devices give rise to
More informationDiscovering Business Insights in Big Data Using SQL-MapReduce
Discovering Business Insights in Big Data Using SQL-MapReduce A Technical Whitepaper Rick F. van der Lans Independent Business Intelligence Analyst R20/Consultancy July 2013 Sponsored by Copyright 2013
More informationwww.objectivity.com Choosing The Right Big Data Tools For The Job A Polyglot Approach
www.objectivity.com Choosing The Right Big Data Tools For The Job A Polyglot Approach Nic Caine NoSQL Matters, April 2013 Overview The Problem Current Big Data Analytics Relationship Analytics Leveraging
More informationOutline. High Performance Computing (HPC) Big Data meets HPC. Case Studies: Some facts about Big Data Technologies HPC and Big Data converging
Outline High Performance Computing (HPC) Towards exascale computing: a brief history Challenges in the exascale era Big Data meets HPC Some facts about Big Data Technologies HPC and Big Data converging
More information