SAP HANA

SAP HANA Overview & Roadmap

Uddhav Gupta,

Sr. Solution Manager, Data Warehousing Platform

Tom Kurtz

Global Practice Director, BI Consulting Services

http://www.sap.com/index.epx

© 2011 SAP AG. All rights reserved. 2This presentation and SAP„s strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. This document is

provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement

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The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the permission of SAP. This presentation is not subject to your license agreement or any other service or subscription agreement with SAP. SAP has no obligation to pursue any course of business outlined in this document or any related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation and SAP's strategy and possible future developments, products and or platforms directions and functionality are all subject to change and may be changed by SAP at any time for any reason without notice. The information on this document is not a commitment, promise or legal obligation to deliver any material, code or functionality. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. This document is for informational purposes and may not be incorporated into a contract. SAP assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent.

All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions.



Analytic

Applications

Governance,

Risk, and

Compliance

Enterprise

Performance

Management

Business

Intelligence

Data

Warehousing

Enterprise

Information

Management

Business analytics solutions from SAPOur approach

Analytic Capabilities

Collaboration

Data Sources Access

Services and Best Practices



Technology that allows the processing of

massive quantities of real time data

in the main memory of the server

to provide immediate results from

analyses and transactions

Vision: In-Memory ComputingBackground and Context



EXPAND PARTNER ECOSYSTEM

Partner-built applications, Hardware partners

CUSTOMER CO-INNOVATION

Design with customers

TECHNOLOGY INNOVATION BUSINESS VALUE

Real-Time Analytics, Process Innovation, Lower TCO

GU

IDIN

G P

RIN

CIP

LE

S

INNOVATION WITHOUT DISRUPTION

New Capabilities For Current Landscape

HEART OF FUTURE APPLICATIONS

Packaged Business Solutions for Industry and Line of Business

SAP Strategy for In-Memory Computing



SAP’s Currently Available In-Memory Solutions

The Business Warehouse Accelerator (BWA) - Accelerates BW Queries by speeding up data acquisition and supporting very specific on-the-fly calculations & aggregations

SAP BusinessObjects Explorer, accelerated version - Combines the speed of BWA with the simplicity of Explorer to gain insights by analyzing large volumes of data

SAP NetWeaver Enterprise Search - Role based secured search solution for structured & un-structured data

SAP CRM Customer Segmentation: Solution for determining target groups for marketing campaigns, slicing through millions of records in fractions of a second

SAP Advanced Planner and Optimizer with liveCache

SAP Business ByDesign analytics

SAP HANA is founded on a history of building in-memory products at SAP



In-Memory Computing – The Time is NOWOrchestrating Technology Innovations

HW Technology Innovations

64bit address space – 2TB in

current servers

100GB/s data throughput

Dramatic decline in

price/performance

Multi-Core Architecture (8 x 8core CPU

per blade)

Massive parallel scaling with many

blades

One blade ~$50.000 = 1 Enterprise

Class Server

Row and Column Store

Compression

Partitioning

No Aggregate Tables

Insert Only on Delta

The elements of in-memory computing are not new. However, dramatically improved hardware economics and technology innovations

in software have now made it possible for SAP to deliver on its vision of the Real-Time Enterprise with in-memory business applications

SAP SW Technology Innovations



Preconfigured Analytical Appliance

■ In-Memory software + hardware

(HP, IBM, Fujitsu, Cisco, DELL)

In-Memory Computing Engine Software

■ Data Modeling and Data Management

■ Real-time Data Replication Data Services for SAP

Business Suite, SAP BW and 3rd Party Systems

Capabilities Enabled

■ Analyze information in real-time at

unprecedented speeds on large volumes of non-

aggregated data

■ Create flexible analytic models based on real-

time and historic business data

■ Foundation for new category of applications

(e.g., planning, simulation) to significantly

outperform current applications in category

■ Minimizes data duplication

SAP High-Performance Analytic Appliance (SAP HANA)Architecture

SQL MDXBICSSQL

SAP HANA studio

Sybase Replication

Server

SAP Business Objects Data

Services

SAP HANA appliance

Other ApplicationsSAP BusinessObjects

BI Solutions

SAP NetWeaver

BW

SAP Business

Suite3rd Party

SAP HANA database

Calculation and Planning Engine

Row & Column Storage



Success with SAP HANA™

Across industries and across the globe

Consumer and

Health Products

Manufacturing

Energy

Communications

and Media

Services

Technology



In-Memory

Appliance

Transactional

System

Data

In-Memory Services

Deployment Considerations

Data Modeling and

Extraction2

In-Memory

Installation &

Management

1BI Consumption

3

Dashboards

Explorer

Analysis

Process for deploying In-memory appliance; involves system architects and administrators with in-memory familiarity 1

Identify respective data considerations based on relevant scenario; involves data modeling, data synchronization2

Development of desired BI front end; reporting, dashboards, other BI outputs3

© 2011 SAP AG. All rights reserved. 11

HANA (SLES 11 SP1)

Admin Workstations (WIN) End users Workstations (WIN)

BOE (Refer to PAM)

Data Services (Refer to PAM)

Data Sources

• SAP IMCE Studio 1.0

• SAP IMCE Clients 1.0 • Data Services Designer • Information Designer • MS Excel 2010• Web access to BI admin tools

• MS Excel 2010• SAP IMCE Clients 1.0

•Web access to BI clients

• SAP IMCE Server 1.0, Client , Studio• SAP HANA Load Controller 1.0 • SAP Host Agent 7.20 • Sybase Replication Server 15.5 + ECDA

•Data Services 4.0•Data Services Job Server• Repository (shared with BOE)

• BI Platform• WebApp server• Repository

SAP ERP System••SAP ERP •SAP Host Agent 7.20• Sybase Replication Agent (HP UNIX, SLES, AIX)

SAP BW System

3rd Party systems

HANA v1.0 Landscape with external systems along with Operating systems & Software installed



ABAP AS

App

DB

ABAP AS Next Generation

Next Generation Apps

SAP HANA

Data in

memoryRuntime

Procedure

code

Program

code

compile

& deploy

Fast data

transfer

Next Generation Applications Overview

Applications – Tight coupling between application server and SAP HANA

Today Mid-Term (Plan)Tight Coupling

With large data volumes,

reading information

becomes a bottleneck

Next generation

applications will delegate

data intense operations

The runtime environment

executes complex

processes in memory

In memory computing

returns results by pointing

apps to a location in

shared memory



SAP HANA Proof-Points

SAP BusinessObjects

and other Applications

SQ

L

MD

X

BIC

S

SAP HANA

SAP ERP

SAP BW

3rd Party

replicate

ETL



3rd Party BI Client

Custom Web

Developed UI

3rd party application

Non-Certified

Business Intelligence Clients and SAP HANA 1.0

ERP

SAP In-memory Computing Engine

Real Time

DB

SAP BW 3rd Party

SAP BusinessObjects

Data Services

SAP HANA (Appliance)

SAP BusinessObjects BI 4.0

Semantic Layer

CrystalWebI Dashboards

Explorer A Office

SQL

(ODBC/JDBC) BICS

Microsoft

Excel

MD

X (

OD

BO

)

Sybase Replication Server

DBSQL

Crystal

Sybase UnwiredSQL

(ODBC/JDBC)



HANA Proof Point

20x Faster Analysis with 200x

Better Price/Performance

Shelf turnaround:

Down to 2 days from 5 days

Eliminated out of stock

scenarios during promotions

© 2011 SAP AG. All rights reserved. 16Confidential

Query Acceleration

Large Bank – 1 Month of Customer Information

6.6

41.9

0 5 10 15 20 25 30 35 40 45

HANA

Traditional DB

Data Volume (GB)

Data Compression with HANA

0 500 1000 1500 2000 2500 3000

Query 1

Query 2

Query 3

3.2

5.1

5.1

1050

1320

2660

Query Run-Time (seconds)

Query Run-Time Comparison

Traditional DB HANA

6.3x Data

Compression

369x Average

Query Speed-Up

No Schema Changes

Same Data

Same SQL

Immediate Benefits



Additional examples for new In-Memory Applications

Financial Services

Hedge fund trading analysis .

Real-time systematic risk management and

reporting based on market trading exposure

Consumer Products Goods

Supplier Risk Management

Inventory Recall Reconciliation Product trace

Product Lifecycle and Cost management

EPA standards compliance

On-Shelf Availability Analysis

Real-time Warranty and defect analysis

Manufacturing

Manufacturing Production and Maintenance

Analytics

Real-time Asset Utilization Analytics

Oil & Gas

Operations Performance Management

Business Transformation

Oil Well Performance Analysis

Supply Chain Network Visibility

Spend Performance Analysis

Retail

Store Operations

Point-of-Sales Retail Sales Analytics

Load Balance Optimization

Real-time completive multi-channel pricing

Product damage, returns and spoilage

And many more ….



In-Memory Analytics■ SAP HANA real-time

operational analytics

■ Complete BI Suite with BI 4

runs on SAP HANA

One Store for Data and

Analytics■ SAP HANA only persistence layer

for SAP Business Suite

■ SAP Business Suite optimized

for in-memory computing

■ Flexible real time analysis

of operations at non-

aggregated level

■ Real-Time operational

planning and simulation

capabilities: link to execution

■ Primary persistence and

optimized for SAP BW

■ Reduced landscape complexity

■ Value chain transformation

Capabilities

Benefits

Next-gen Applications■ SAP BW fully running on SAP

HANA

■ SAP HANA platform for in-

memory apps

■ SAP Business Suite runs on

SAP HANA

■ Further optimization of BI 4

Suite for SAP HANA

■ Industry and LOB Analytic Apps

“Innovation“

Mid-Term (Plan) “Transformation”

Longer-Term (Plan)

SAP In-Memory StrategyProduct Strategy and Plan

“Renovation”

SAP HANA 1.0

Ramp-Up since Dec 2010



Enterprise Data Warehouse

Corporate BI

Database

Local BI

SAP ERP 1(or CRM, SRM, SCM)

Database

Data

Mart

DBETL

BI

SAP ERP n(or CRM, SRM, SCM)

Database

Data

Mart

DBETL

BI

Non SAP

Buss App

Database

Data

Mart

DB

. . .

This presentation outlines our general product direction and should not be relied on in making a purchase decision.

Today‘s Situation



Enterprise Data Warehouse (BW)

Corporate BI

Database

Local BI


DatabaseSync

x


Database

SAP

HANA

1.0

Non SAP

Buss App

Database

SAP

HANA

1.0

. . .

BWA

SAP

HANA

1.0


Step 1 – SAP HANA 1.0



SAP Business Application

Database

SAP HANA

BI

Data replication

near real-time

No more query workload

from reports on the database

Flexible reporting with SAP

BI tools and extreme performance

No change in

the application

Use case – Operational Reporting




Corporate BI


Database


Database

Non SAP

Bus App

Database

. . .

SAP HANA (nxt)

Virtual

Data Mart

Virtual

Data Mart

Virtual

Data Mart

Local BI


Step 2 – Primary Persistence for BW




Corporate BI


Database


Database

Non SAP

Bus App

Database

. . .

SAP HANA (nxt)

Virtual

Data Mart

Virtual

Data Mart

Virtual

Data Mart

Local BI New Applications


Step 3 – New Applications



Corporate BI

Non SAP

Bus App

Database

SAP HANA

Virtual

Data Mart

Virtual

Data Mart

Virtual

Data Mart

Local BI New Applications

ERP 1 ERP nEDW

(BW). . .


Step 4 – Future Application Stack (vision)

© 2011 SAP AG. All rights reserved. 25Confidential

“By 2012, 70% of Global 1000 organizations will load detailed data

into memory as the primary method to optimize BI application

performance.”

- Gartner

Thank You!

© 2011 SAP AG. All rights reserved. 62

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© 2011 SAP AG. All rights reserved

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