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    SAP HANA:

    In-Memory Data Management

    for Enterprise Applications

    Dr. Alexander Zeier

    Massachusetts Institute of Technology (MIT)VisitingProfessor

    March 23rd 2012SAP Academic Conference Americas, San Antonio

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    The Vision by Prof. Hasso Plattner

    Transactional (OLTP) and analytical

    (OLAP) data processing has to be on one

    system again

    Enterprise applications have to reflectlatest developments in:

    Hardware, such as:

    Multi-core processors

    Huge Main Memory

    Data management, such as: Column-oriented storage

    Light-weight compression

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT2

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    In-Memory Data Management

    Advancesin Hardware

    64bit addressspace 2TB incurrent servers

    100GB/s datathroughput

    Dramatic decline inprice/performance

    Multi-Core Architecture(8 x 10core CPU per blade)

    Parallel scalingacrossblades

    Oneblade ~$50.000 = 1Enterprise Class Server

    Advancesin Software

    +

    RowandColumnStore

    Compression Partitioning No AggregateTables

    +

    +

    ++

    Insert Only

    4

    A

    On-the-flyextensibility

    +

    + +

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT

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    Any attributeas index

    Insert onlyfor time travel

    Combined columnand row store

    +

    No aggregatetables

    Minimalprojections

    Partitioning

    Analytics onhistorical data

    t

    Single andmulti-tenancy

    SQL interface oncolumns & rows

    SQL

    Reduction oflayers

    x

    x

    LightweightCompression

    Multi-core/parallelization

    5

    On-the-flyextensibility

    +

    + +

    Active/passivedata storeP

    A

    Bulk load

    +

    +

    ++

    TText Retrieval andEXploration

    Object torelationalmapping

    Dynamic multi-threading withinnodes

    Map reduce No diskGroup Key

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MI

    T

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    RowStore

    ColumnStore

    Row vs. Column

    Store

    Row4

    Row3

    Row2

    Row1

    Two Different Principles of PhysicalData Storage: Row vs. Column Store

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT6

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    Accessing Enterprise Data

    Column StoreRow Store

    7

    SELECT *

    FROM Sales OrdersWHERE Document Number = 95779216(OLTP-style query)

    SELECT SUM (Order Value)FROM Sales OrdersWHERE Document Date > 2009-01-20(OLAP-style query)

    Row4

    Row3

    Row2

    Row1

    Row4

    Row3

    Row2

    Row1

    DocNum

    DocDate

    Sold-To

    ValueStatus

    SalesOrg

    DocNum

    DocDate

    Sold-To

    ValueStatus

    SalesOrg

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT

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    DictionaryCompression

    8

    Reduces I/O operations to main memory (bottleneck) Operations directly on compressed data

    Dictionaries

    8

    Typical compression factor for enterprisesoftware 10

    In financial applications up to 50

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT

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    Table Characteristics

    Row Store Column StoreSmall tables

    Frequent updatesMaterialized aggregates

    Large tablesRare updates

    Dynamic aggregates

    Transactional

    Data

    Historical

    DataDirect access to tuplesBlade-local transactions

    Status updatesActive / passive

    Sequential accessNo updates

    9

    TextCrawler

    Join structured &unstructured data

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT

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    InnovativeIn-Memory / HANA

    Applications

    10 In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT

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    Customer Study 1:

    Dunning Run in < 1s?

    Dunning run determines all open anddue

    invoices Customer defined queries on 250M records

    Current system: 20 min

    New logic:1.5 sec In-memory column store Parallelized stored procedures Simplified Financials

    13 In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT

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    Dunning Application

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    GORFIDTracing pharmaceutical

    packages in Europe 15 bnpackages / 35 bn

    read events per year

    Prototype with12 billions

    records withresponse time:

    23 ms

    15

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    HANA Oncolyzer

    Medical doctors have all patientdata at hand to applypersonalized medicine

    Medical researchers performreal-time analysis to definecohorts for clinical studies

    International research initiativefor exchanging relevant tumor

    data started at World Health Summit 2011 in Berlin

    In-Memory Technology as key-enabler for real-time analysis

    provider for information at your fingertips (iPad)In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT16

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    HANA Oncolyzer - combiningStructured and Unstructured Data

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT17

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    HANA Oncolyzer was presented onCeBIT 2012 to Germanys Chancellor

    Angela Merkel as SAP s Innovation 2012

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT18

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    First Results of Customers

    using SAP HANA

    1,000x Faster: Many (Dunning, Aging, ) 10,000xFaster: NongFuSpring, Essar Group, SAP IT,

    Cornell, Charmer Sunbelt 100,000X Faster: YodoBashi, MKI

    OR

    24+ Hours to 3.8S: Food and Beverage / Distribution - Logistics

    15+ Hours To 4.8S: Project Management /Services, Profitability, Performance

    30 Days to 28S: Manufacturing Order to Cash 3 Days to 2s: Retail / Insurance Incentives

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT19

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    All Findings are Summarized in theBook In-Memory Data Management

    This book is the culmination of five years worth ofin-memory research

    PART I An Inflection Point for Enterprise Applications

    Overview of our vision of how in-memory technology willchange enterprise applications

    PART II A Single Source of Truth through In-Memory Technical foundations of in-memory data management

    In-depth description of how we intend to realize our vision

    PART III How In-Memory Changes the Game

    Resulting implications on the development and capabilities ofenterprise applications

    -> Book launched at Cebit 2011, SAP Product HANA is available sinceJune 2011.

    -> New extended BookEdition In-Memory Data Management -Technology and Applications focusing onApplicationDevelopment will be available for Sapphire May 2012.

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT20

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    In-Memory/HANADrives Worldwide Innovation

    Book Launch at CeBIT 2011 with Vice-President oftheEuropean CommissionNeelieKroes

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT21

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    SAP andHPI win theGerman Innovation Award 2012

    for SAP HANA!This years winners were announced amMarch 16, 2012 in Munich, Germany.

    Pleasefeel freeto contact me:

    Dr. Alexander Zeier

    Massachusetts Institute ofTechnology (MIT)VisitingProfessorExecutive Director MIT Forum for SC InnovationEmail:[email protected] with list of over150 Publications: http://zeier.mit.edu

    In-Memory/HANA Enterprise Data Management | SAP UA Conference | March 23rd 2012 | Dr. Alexander Zeier, MIT