Sap Hana

SAP HANA

SAP HANA® Technical Overview

Driving Innovations in IT and in Business
with In-Memory Computing Technology

SAP HANA TecHNicAl Overview

Table of Contents
4

introduction

5

SAP HANA Platform

6

SAP HANA Appliance Software

7

12

SAP HANA Database

Deployment Scenarios for SAP HANA
Operational Data Mart
Agile Data Mart
Architected Data Mart
SAP HANADatabase for SAP NetWeaver
Business Warehouse

SAP HANA Database Administration

SAP HANA Database for SAP Business
Suite Accelerators

9

Sizing for the SAP HANA Database

SAP HANA Database for In-Memory
Business Applications

10

Data load Architecture Scenarios for SAP HANA

SAP HANA Database for Core
SAP Business Suite Applications

Near-Real-Time Replication with
SAPLandscape Transformation
Real-Time Replication with Direct Write
Extraction/Periodic Load

SAP HANA Application Cloud

14

Data Analysis in SAP HANA

16

information Modeling in SAP HANA
Agile Data Modeling with the
Information Composer
Dynamic Data Modeling with the
Information Modeler

17

Outlook
Find Out More

About the Authors
Erich Schneider is a senior director in thePremier Customer Network (PCN) and has been implementing SAP® solutions for
over 20 years. He was chief architect in the internal SAP program to enable data and business intelligence (BI) architecture
using SAP in-memory computing technology across all SAP lines of business worldwide.
Raghav Jandhyala is a solutions expert for the SAP HANA® platform in the SAP Customer Solution Adoption (CSA)group,
focusing on early customer adoption of innovations from SAP for strategic industries. Prior to joining CSA, Raghav was a
solution manager for the SAP Banking group, where he supported go-to-market activities for SAP HANA in the banking
industry.

TAkiNg Full ADvANTAge OF SAP® iN-MeMOry cOMPuTiNg TecHNOlOgy

Introduction
The announcement of the SAP HANA® platform has created a lotof buzz in the IT and
business world. As new business demands
challenge the status quo, the scale is larger,
expectations are greater, and the stakes are
higher. New-breed IT systems must be able to
evaluate, analyze, predict, and recommend –
and do so in real time. An in-memory approach
is the only way to tackle a real-time-data future
that includes new data types such as social
mediamonitoring and Web-automated sensors
and meter readings.
Today’s business users need to react much more quickly to
changing customer and market environments. They demand
dynamic access to raw data in real time. SAP HANA empowers
users with flexible, on-the-fly data modeling functionality by
providing nonmaterialized views directly on detailed information. SAP HANA liberates users from the waittime for data
model changes and database administration tasks, as well as
from the latency required to load the redundant data storage
required by traditional databases. The elimination of aggregates and relational table indices and the associated maintenance can greatly reduce the total cost of ownership.
Some use the term “in-memory” in the context of optimizing
the I/O access with databasemanagement, centering on
accessing data from the hard disk by pre-storing frequently
accessed data in main memory. The term is also used for a traditional relational database running on in-memory technology.
Some solutions offer columnar storage on traditional hard-disk
technology, while other platforms offer the option of storing
data on solid state disks (SSD). Although these disks have nomoving parts and access data much more rapidly than hard
disks, they are still slower than in-memory access.

Only SAP HANA takes full advantage of all-new hardware
technologies by combining columnar data storage, massively
parallel processing (MPP), and in-memory computing by using
optimized software design.
Many SAP customers have already successfully deployed SAP
HANA to drive...