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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 |
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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
+
+ +
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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 |
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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
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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 |
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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 |
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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
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InnovativeIn-Memory / HANA
Applications
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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
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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
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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 |
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HANA Oncolyzer - combiningStructured and Unstructured Data
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HANA Oncolyzer was presented onCeBIT 2012 to Germanys
Chancellor
Angela Merkel as SAP s Innovation 2012
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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
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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.
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In-Memory/HANADrives Worldwide Innovation
Book Launch at CeBIT 2011 with Vice-President oftheEuropean
CommissionNeelieKroes
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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
