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Run Better With Game-Changing Innovations For IT:  Faster Business Analytics: The road to analysing business as it happens with new in-memory technology
 

Run Better With Game-Changing Innovations For IT: Faster Business Analytics: The road to analysing business as it happens with new in-memory technology

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Faster Business Analytics: The road to analysing business as it happens with new in-memory technology

Faster Business Analytics: The road to analysing business as it happens with new in-memory technology

Carl Streatfield

Run Better with Game-Changing Innovations for IT

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    Run Better With Game-Changing Innovations For IT:  Faster Business Analytics: The road to analysing business as it happens with new in-memory technology Run Better With Game-Changing Innovations For IT: Faster Business Analytics: The road to analysing business as it happens with new in-memory technology Presentation Transcript

    • SAP In Memory TechnologyCarl StreatfieldMay 2011
    • DisclaimerThis presentation outlines some product directions and should not be reliedon in making a purchase decision. This presentation is not subject to yourlicense agreement or any other agreement with SAP. SAP has no obligation topursue any course of business outlined in this presentation or to develop orrelease any functionality mentioned in this presentation. This presentationand SAPs strategy and possible future developments are subject to changeand may be changed by SAP at any time for any reason without notice. Thisdocument is provided without a warranty of any kind, either express orimplied, including but not limited to, the implied warranties ofmerchantability, fitness for a particular purpose, or non-infringement. SAPassumes no responsibility for errors or omissions in this document, except ifsuch damages were caused by SAP intentionally or grossly negligent.© 2011 SAP AG. All rights reserved. 2
    •  “I need the answer now” “I don‟t have time” “Gut feel is a lot faster” Intuitive Speed Experience Information
    • In-Memory Computing allowsmassive quantities of real time data running in the main memory of the server to provide immediate results HANA – SAP Appliance
    • WHAT’S THE TECHNICAL BACKGROUND?© 2011 SAP AG. All rights reserved. 5
    • CPUs do not get Faster© 2011 SAP AG. All rights reserved. 6
    • Memory and Storage Prices (1955-2010) http://www.jcmit.com/mem2009.htm© 2011 SAP AG. All rights reserved. 7
    • Why Now?Has technology caught up with demand? Technology Drivers 1990 2006 Improvement CPU 0.05 7.15 143x MIPS/$ MIPS/$ Memory 0.02 5 250x MB/$ MB/$ Addressable Memory 216 264 248x Network 100 10 Speed Mbps Gbps 100 x Disk Data Transfer 5 130 25x MBPS MBPS© 2011 SAP AG. All rights reserved. 8
    • Why Now? advances in technology• Processor speeds peak • Old central bus architecture• Move to multi-core • Now memory controller on chips • Memory Prices fall© 2011 SAP AG. All rights reserved. 9
    • Pivotal Moment in Technology Affordable Memory Innovation  Disk-based row-stores were and are optimized for the disk I/O bottleneck  The advances in hardware of the last two decades allow to fundamentally rethink this basic design goal© 2011 SAP AG. All rights reserved. 10
    • In-Memory an Obvious Paradigm? ! ? Databases  Most databases were written in the late 80s  Designed to reliably persist data on disk A A A A  All DB concepts center around overcoming latency when A A A A reading or writing data to or from disk IOIIOOIO  OLAP was introduced later, to overcome significant OOIOIIOI performance IOIOIOIO issues when querying databases for data analysis IIIOOOIO Renovation in 2010?  Store data only on fast outer rings of disks? Lots of Memory Database for data  Add logic on disks to enhance information throughput? Lots of DataCache data in memory  Cache information in memory whenever possible?There is more potential in this new technology than just doing the same thing now in memory! © 2011 SAP AG. All rights reserved. 11
    • In-Memory Computing – The Time is NOW Multi-Core Architecture (8 x 8core CPU 64bit address space – 2TB in per blade) current servers A Massive parallel scaling with many 100GB/s data throughput blades Dramatic decline in One blade ~$50.000 = 1 Enterprise price/performance Class Server HW Technology Innovations SAP SW Technology Innovations + + + ++Row and Column Store Compression Partitioning No Aggregate TablesInsert Only on Delta © 2011 SAP AG. All rights reserved. 12
    • HANAWhat do we have now?
    • Existing Technology: BWARDBMS vs BWABWA is not a generic SQL databaseBWA is tailored towards a sweet spot of analytic functionalityPerformance management is part of that sweet spot performance performance  generic model  highly customized aggregation  generic querying capability  queries against predefined BWA star schema patterns RDBMS functionality functionality© 2011 SAP AG. All rights reserved. 14
    • In MemoryWhat do we have now?what„s coming soon?
    • Stepwise Implementation for Immediate Value at Low Risk Today„s System Landscape  ERP System running on traditional database  BW running on traditional database  Data extracted from ERP and loaded into BW  BWA accelerates analytic models  Analytic data consumed in BI or pulled to data marts Step 1 – In-Memory in parallel  Operational data in traditional database is replicated into memory for operational reporting  Analytic models from production EDW can be brought into memory for agile modeling and reporting  Third party data (POS, CDR etc) can be brought into memory for agile modeling and reporting© 2011 SAP AG. All rights reserved. 16
    • Stepwise Implementation for Immediate Value at LowRisk Step 2 – Primary Data Store for BW  In-Memory Computing used as primary persistence for BW  BW manages the analytic metadata and the EDW data provisioning processes  Detailed operational data replicated from applications is the basis for all processes Step 3 – New Applications  New applications extend the core business suite with new capabilities  New applications delegate data intense operations entirely to the in-memory computing  Operational data from new applications is immediately accessible for analytics – real real time© 2011 SAP AG. All rights reserved. 17
    • Stepwise Implementation for Immediate Value at Low Risk Step 4 – Real Time Data Feed  Applications write data simultanously to traditional databases as well as the in- memory computing (real real time for all applications) Step 5 – Platform Consolidation  All applications (ERP and BW) run on data residing in-memory  Analytics and operations work on data in real time  In-memory computing executes all transactions, transformations, and complex data processing© 2011 SAP AG. All rights reserved. 18
    • Thank You!Contact information:Carl Streatfieldcarl.streatfield@sap.comSAP (UK) Ltd