SAP HANA – A Technical Snapshot

~ Debajit Banerjee
Consultant
February 16th, 2011
San Jose, California
©Copyright – Debajit Banerjee, 2011 1

2
SAP High-performance ANalytic Appliance(HANA)
is a pre-configured Analytic Appliance.
So, if you order SAP HANA, you will get In-Memory software
bundled with hardware delivered directly from the hardware
partner.
SAP HANA certified H/W partners : HP, IBM, Fujitsu, Cisco
Software : SAP In-Memory Computing Engine (IMCE) and
Tools for data modeling, data and life cycle management,
security, operations, etc.
HANA will work with Data replication, ETL, and BI.
HANA supports multiple interfaces.
SAP HANA provides
- Operational and Analytical Data mart scenarios
-Access and Analyze Real-Time Information
for high volume of data with the following key features:
- High Performance
- Flexible Analytic Models
- Minimum Data Duplication
- Ease of Use
- Low TCO and Risk
HANA enables organizations to analyze their business operations, based on huge volumes of transactional
information, as business happens. It is a move from ‘After-Event Analysis’ to ‘Real-Time Decision Making’.
©Copyright – Debajit Banerjee, 2011

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In-Memory Computing is a 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.
Why the need for In-Memory Technology?
For Conventional Databases - READ Data Access
Speed from DISK : 5 milliseconds
IT Challenges Business Challenges
Data Explosion Inadequate access to real
time operational
information
High Costs to increase
physical limit for handling
data volumes
Need to react faster to
events impacting
operations for the
dynamic business
changes
High TCO for
infrastructure
management
Unable to blend analytics
and operations as
planning, forecasting,
financial close processes,
etc are based on not real
time information
Dissatisfied business
users
- Processing & analysis
results delayed
- Data is not real time
For In-Memory Databases - READ Data Access Speed : 5 nanoseconds; simply 1 Million times FASTER

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Traditional concept is changing.
Distribution of data –Linear scalability enabled by
massive parallel workload execution; minimize data
movement
Calculation models –extreme performance and flexibility
with calculations on the fly
Classic Database In-Memory Database
Presentation
Orchestration
Calculation
Data
Presentation
Orchestration
Calculation
Data
User Interface
Layer
Application
Layer
Database Layer
In-Memory Computing Engine is the heart of SAP HANA that offers data acceleration and management
software in a single integrated environment.
It leverage SAP's latest in-memory technologies based on columnar databases, massively parallel
processing (MPP), in-memory computing, and data compression techniques.

Before SAP HANA After SAP HANA
Any Comparison between SAP BWA and SAP HANA 1.0?
Although, there are some similarities(Column store, Aggregation Engine) between these two but HANA is
technically far more than BWA – i) standard interfaces (SQL, MDX), ii) real persistence layer, iii) Row
Store(P*time), iv) transactions (MaxDB), v) SQL parser (P*time), ….
HANA 1.0 is intended as a Data Mart.
On the other side, one can only load InfoCubes into BWA and all the other associated things (complex logic,
defining data model, analysis authorizations) can be done on BW as BWA has BW on top.

Here it is the complete
architectural view of SAP
HANA 1.0 components.
6
simplistic view
different use-case view

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Data Modeling involves :
In-Memory Computing Studio
•Modeling
In-Memory Computing Engine
•Metadata Manager
Business Objects Enterprise
•Data Services
•Data Services Designer
•SBO Information Design Tool
Reporting involves :
In-Memory Computing Engine
•Relational Engines
- Row Store
- Column Store
•Request Processing/Execution Control
- SQL Parser
- SQL Script
- Calculation Engine
- MDX
Business Objects Enterprise
•SBO BI4 Servers (prog for client)
Clients
•SAP BI4 Universes
•BI4 Explorer
•BI4 Analysis
•MS Excel
•Dashboard Design
Administration involves :
In-Memory Computing Studio
•Administration
Persistence Layer
•Page Management and Logger
Disk Storage
•Data Volumes and Log Volumes

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ROW Store is the
relational engine to
store data in row
format.
- Pure in-memory store
(Future versions will
also have an option of
disk based store)
- In memory object
store (in future) for live
cache functionality
- Transactions Version
Memory is the heart of
row store

9
Column Store
- improves read functionality significantly
- also improves write functionality using
asynchronous merge for delta storage
- highly compressed data
- no real files, virtual files
- compression by create dictionary and
applying further compression methods
- merge operation can also be triggered
manually with an SQL command

Appliance Sizes OS Processor CPU Cores Memory Log Storage Vol. Data Storage Vol.
Small SLES11 SP1 Nehalem-EX 2 CPU x 8 256 GB 320 GB 1 TB + SQ*
Small+ (Scale up) SLES11 SP1 Nehalem-EX Up to 4 CPU x 8 256 GB - 512 GB 320 GB – 640 GB (1 TB – 2 TB) + SQ
Medium SLES11 SP1 Nehalem-EX 4 CPU x 8 512 GB 640 GB 2 TB + SQ
Medium+ (Scale up) SLES11 SP1 Nehalem-EX Up to 8 CPU x 8 512 GB - 1 TB 640 GB – 1.2 TB (2 TB – 4 TB) + SQ
Large SLES11 SP1 Nehalem-EX 8 CPU x 8 1 TB 1.2 TB 4 TB + SQ
X-Large / Scale out SLES11 SP1 Nehalem-EX N-times Large Configuration
As of today, OS and Processor is fixed for SAP HANA; OS:SUSE Linux Enterprise Server 11 SP1, Processor: Intel Xeon 7560,
code name Nehalem-EX. *SQ = Stable Queue i.e., Storage used by Sybase Replication server when target is slow or
down; For <5GB, 5GB-20GB, >20GB Data Loads/hr. using 4-8GB Memory with 1Gbps Network, Storage reqd. 100GB, 100-
500GB, 500GB+ respectively.
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Network Requirements Storage Requirements
Internal Disk External Storage
1 Gbps dedicated network between ERP & HANA (10 Gbps optional)
3 x 1 Gbps dedicated networks for BI client access, data & appliance management
OR
1 x 10 Gbps network with VLAN setup for all of the above including the network
between ERP & HANA
For Scale out configuration only:
- 10 Gbps dedicated network between the clustered servers / blades
- 10 Gbps dedicated network between HANA nodes & external storage
Redundant infrastructure for high availability & failover (IP paths, NICs etc.)
Rack servers with internal
disks: PCIe-Flash/ SSD for
LOG volume (100k IOPS)
Scale out configurations
with external storage: 100k
IOPS for LOG volume (e.g.
via external SSD RAID)
SAS / SSD for DATA volume
(800MB-1GB/s sequential
read, min. 10k rotational
speed for SAS drives)
800MB-1GB/s sequential
read for DATA volume (e.g.
via SAS or FC drives 10k
rotational speed min.)

Access End User
Clients via Browser
SBOP Enterprise
 SBOP BI Platform
 SBOP BI Clients
(Explorer, Xcelsius, Dashboard)
SAP Landscape with
SAP BusinessObjects
Portfolio (SBOP)
SAP HANA Data
Providers
SAP ERP System
Admin Client End User Client
 SAP IMCE Studio 1.0
 SAP IMCE Client 1.0
 SAP IMCE Client 1.0
 MS Excel
SAP HANA System
 SAP IMCE Server, Client, Studio 1.0
 SAP HANA Load Controller 1.0
 SAP Host Agent 7.20
 SYBASE Replication Server 15.5 and
Enterprise Connect Data Access (ECDA)
 SAP Host Agent 7.20
 SYBASE Replication Agent
SAP BW System
Non-SAP System
SAP BusinessObjects Portfolio (SBOP)
Data Services
 DS Designer
 DS Job Server

 Agile Scenarios
- Operational Data Mart
- Agile Data Mart
 can be used in Industries
• Banking
• CPG
• Retail
• Utilities
• Telco
• Hi-Tech
 Lines of Business
 CO-PA
 ERP
 HCM
 CRM
 Finance

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Today’s SAP Landscape;
It is relatively a complex
one with traditional SAP
ERP, BI and Data
Warehousing.
SAP ERP 1
(or CRM, SRM, SCM)
Data
Mart
Corporate BI
Enterprise Data Warehouse (BW)
DB
DB
SAP ERP n
(or CRM, SRM, SCM)
DB
Non-SAP
Business
Appl.
DB
DB
Data
Mart
DB
Data
Mart
DB
Local
BI
BI BI
ETL ETL
Corporate BI
DB
SAP ERP 1
(or CRM, SRM, SCM)
DB
SAP ERP n
(or CRM, SRM, SCM)
DB
Non-SAP
Business
Appl.
DB
Local
BI
Sync Sync
HANA
1.0
HANA
1.0
HANA
1.0
BWA
SAP HANA 1.0 enables zero
latency reporting and analytics
against side-by-side with SAP
ERP. It is the first movement
towards ‘Real-Time Decision
Making’.
BWA provides general
performance improvement for
SAP BW.

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SAP HANA – FUTURE :
BWA evolves into SAP HANA X.X
as SAP in-memory computing
becomes the primary
persistence mechanism for BW.
SAP ERP 1
(or CRM, SRM,
SCM)
SAP HANA – VISION :
OLTP and OLAP Convergence
Corporate BI
HANA X.X
DB
SAP ERP n
(or CRM, SRM,
SCM)
DB
Non-SAP
Business
Appl.
DB
Local BI Virtual
Data
Mart
New
Application
Virtual
Data
Mart
Virtual
Data
Mart
Corporate BI
Non-SAP
Business
Appl.
DB
ERP 1 ERP n EDW
(BW)
HANA
Local BI Virtual
Data
Mart
Virtual
Data
Mart
Virtual
Data
Mart
Now Future Trend
SAP HANA 1.0
Data Mart next to
ERP
No BW or BWA
BWA
BI on top of a
corporate
EDW(BW)
SAP HANA
1.5
SAP HANA
2.0
New
Application

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(1) ERP and BW can be connected to HANA using Data Services or Sybase Replication Server
(2) No name space concept in HANA 1.0 at this moment, current release does not support
connecting to several ERP instances. However this issue can be avoided using data sources.
(3) CRM also can use HANA
(4) Data from BW into HANA can be loaded into using Data Services and Infospokes
(5) BWA Hardware can be upgraded to HANA given that hardware is relatively new
(6) BWA Licenses can be transferred to HANA
(7) SAP BOBJ tools can directly report HANA
(8) HANA supports BICS (Business Intelligence Consumer Services) interface
(9) External tools can connect to HANA using JDBC and ODBC drivers
(10)HANA currently doesn't support complete MDX set, it supports EXCEL 2010 standard MDX
(11)SQL Script, MDX statements are passed to optiomizer which is included in calculation engine; it
generally breaks up a model into sub processes for optimized performance on cost based.
(12)Planning Engine Will be included in next release. It will include planning functions like distribute
and copy functions.

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Key Benefits delivered by SAP HANA as follows :
(1) Real-Time Decision Making
 Fast and easy creation of ad-hoc views on business; enabling a 360 degree view of the business
 Access of Real time analysis from “What happened yesterday”
 Close to zero latency
(2) Accelerate Business Performance
 Increase speed of transactional information flow in areas such as planning, forecasting, pricing, offers…
(3) Unlock New Insights
 Remove constraints for analyzing large data volumes – trends, data mining, predictive analytics, etc.
 Structured and unstructured data
(4) Improve Business Productivity
 Business designed and owned analytical models
 Business self service which in turn reduces reliance on IT
 Use data from anywhere
(5) Improve IT efficiency
 Manage growing data volume and complexity efficiently
 Lower landscape costs
 Non-Disruptive to the existing EDW strategy

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References :
SAP website
http://www.sap.com
http://www.sap.com/platform/in-memory-computing/index.epx
SAP SDN website
http://www.sdn.sap.com/irj/sdn/index?language=en
SAP ASUG website
http://www.asug.com

Row Store Architecture
Currently not present in HANA 1.0

Column Store Architecture
Currently not present in HANA 1.0

Importance of Persistence Layer

SAP In-Memory Computing
Studio and Modeling

© Copyright – Debajit Banerjee, 2011.
All rights reserved.
Disclaimer
SAP, HANA, R/3, ERP, BW, BI, SAP NetWeaver, and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered
trademarks of SAP AG in Germany and in several other countries all over the world. All other product and service names mentioned are the trademarks of their
respective companies.
Data contained in this document /presentation serves informational purposes only. It is purely made for educational or knowledge-sharing, non-commercial purpose.
I have used SAP's slides or information within this presentation as there is not so much information available for this topic or business line, as of today. I cannot be held
responsible for the information related to third parties. I have no obligation to pursue any course of business outlined in this presentation or to develop or release any
functionality mentioned in this presentation. This 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.
I reserve the right to change the published information without prior notice. I expressly disclaim liability for any damage arising out of or in any way connected with this
document.
If you have any questions or concerns about the information published in this document, please get in touch with me for clarification.

SAP HANA – A Technical Snapshot

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