Developing and Deploying Applications on the SAP HANA Platform

Developing and Deploying Analytic
and Transactional Applications on the
SAP HANA Platform
Vitaliy @Sygyzmundovych Rudnytskiy, SAP
SAPinsider HANA2015 Nice, June 2015
@SAPDevs #SAPHANA

© 2015 SAP SE or an SAP affiliate company. All rights reserved. 1
Let’s start with…
- … introduction :)
- Vitaliy Rudnytskiy
@Sygyzmundovych
- SAP’s Developer Relations team
- 12 years as a BI Technology Consultant
- SAP Mentor 2010-2014
- Self-proclaimed King of Data Geeks 
- Based in Wrocław

Agenda
10 Introduction()
20 SELECT "Key_Features" FROM SAP.HANA
30 Top Reasons -> Choose("SAP HANA")
40 SELECT Flexible_Choices FROM SAP.HANA
50 Wrap_Up()

Custom Applications Are Key to Modern IT
Organizations seek to provide
innovative technology and
capabilities where it helps them
compete and impact the
business, while accepting more
standardized packaged solutions
in areas that do not necessarily
require differentiating capabilities.
IDC
IT-developed applications have
become the primary driver for
growth and differentiation for
enterprises. The building of these
custom agile applications is
becoming a hallmark of the new
digital enterprise. Accenture
Vision, 2014
Forrester Research: Don’t Just Maintain Business Applications, Raise Business Responsiveness, 2014
“
”
Packaged
Applications
26% App
Maintenance
49%
Custom
Applications
25%
Business Software Spending*

SAP HANA: In-Memory Platform for All Applications
JSONR Open ConnectivityMDXSQL
Consumer-grade
experience
Application Services
Database Services
Integration Services
Social Network
Data
Geospatial
Data
SAP HANA Platform
Machine
Data
Text
Data
Structured
Data
For Cloud and On-Premise
Open Interfaces
In-Memory
OLTP & OLAP
All Data – one copy
Embedded Libraries

Typical Application
Architecture
HANA as a Fast Data
Engine
HANA as an
Integrated Platform
Architectural Options to Use SAP HANA Platform
Each Layer Takes Care of Partial Tasks of an Application
Data Ingestion
Business Logic
Presentation logic
Data Process
Data Storage DB
Client
Application
Server
Application
Server
Application
Server
DB
Application
Server
Client
SAP HANA
In-Memory
Platform
Client
SAP HANA
In-Memory
Platform
Development,
crowd source
… the project
is great
Development,
crowd source
… the project
is great
Development,
crowd source
… the project
is great

Innovation Previously Unfeasible
Mitsui Knowledge Industry – Cancer Cell Genomic Analysis
Goal: transform comprehensive patient
care to fight against cancer
 Reduce the time to detect variant DNA
 Support personalized patient
therapeutics
 DNA results 216x faster – in 20 minutes
or less
Streamline process of providing
individualized cancer drug
recommendation

Developer Licenses to Get Started
UseDevelopLearn
Trials/Sandboxes
Free, time-limited
development environments
Developer Licenses
Full development
(free license,
hosting costs may occure)
Commercial
Licenses
For Customers and Partners
Free
Charge

SAP Developer Center: http://developers.sap.com
• One-Stop Shop for SAP Developers
• Structured by developer topics, including SAP HANA
• Guided developer experience
• Access to developer editions of SAP platforms and tools
• Integrated with SAP.com and SCN  migrating towards 1DX

Helping you to get started with new SAP technologies
SAP CodeJam is a 5 to 6 hours hands-on coding and
networking event where attendees share their
knowledge and collaboratively develop with SAP
technologies, platforms and tools in a fun and casual
environment.
The events are developer community focused and
supported by SAP, exploring technologies available
through the SAP Developer Center.
For more details on the CodeJam program or the
multiple topics we offer, check out our page here:
http://scn.sap.com/docs/DOC-37775

openSAP Cources: http://open.sap.com
Keeping pace with the rapidly developing world of information technology is a need
that SAP helps to fill with openSAP
openSAP is developed and provided by SAP in cooperation with the Hasso Plattner
Institute
openSAP works according to the principle of "Massive Open Online Courses" (MOOC),
but is not the replacement for formal SAP Education or SAP certification
Some recent courses:
Software Development on SAP HANA (Delta SPS 09)
Build Your Own SAP Fiori App in the Cloud
ABAP Development for SAP HANA

SELECT "Key_Features" FROM SAP.HANA
Key SAP HANA Features for Application Development

SAP HANA Components for Application Development
SQL JSON .NET J/ODBC OData HTML5 MDX XML/A R
Database Services
Graph
Data
Geospatial
Data
SAP HANA Platform
Machine
Data
Text
Data
Structured
Data
For Cloud and On-Premise

SAP HANA XS Engine
Native SAP HANA Application Fully Leveraging In-Memory Computing
SAP HANA
Client
Applications running on SAP HANA XS Engine that:
 Provide powerful search services and built-in web server to
access static content stored in SAP HANA repository
 Optimize database connector to access in-memory data faster
 Support attractive and dynamic HTML5 UI via OData services
or by writing native application-specific code that runs in SAP
HANA context
Application development following a layered
approach
 UI rendering completely in the client (browser, mobile apps)
 Server-side procedural logic in JavaScript
 All artifacts stored in the SAP HANA repository
Presentation
logic
Control flow
logic
Calculation logicData
XS

Sample of some cool ideas from the community
„A Simple Door Monitoring System with HANA XS and Raspberry Pi”
by Ferry Gunawan
http://scn.sap.com/community/developer-center/hana/blog/2014/07/09/build-a-door-sensor-with-raspberry-pi-and-hana

SAP HANA Smart Data Streaming
• Capture, filter, analyze, and act on
millions of events per second in real time
• Capture high value data in HANA and
direct other data into Hadoop
• Stream live information to operational
dashboards
• Perform continuous queries using
declarative (CCL) or model-driven
approaches
Incoming
streams
Stream
(push)
SAP HANA
Streaming
Service

„HANA Smart Data Streaming in Action” by Eric Du
http://scn.sap.com/community/developer-center/hana/blog/2015/03/17/hana-smart-data-streaming-in-action

SAP HANA Predictive Analysis
1 Predictive Analysis Libraries (PAL)
Accelerate predictive analysis and
scoring with native, in-database
algorithms delivered out-of-the-box
Graphical Modeling
Pre-built commonly utilized business &
predictive algorithms to facilitate a faster
and easier development
2 R Integration
Execute R scripts via high performing
parallelized connection. Embed R
scripts as part of overall query plan.
Client Tools
SAP Predictive Analysis,
SAP InfiniteInsight,
BI clients: SAP Lumira
Partner Tools: SAS
SAP Industry &
LoB Applications
Demand Signal Management, Fraud
Management, Audience Discovery &
Targeting, over 20 other Apps
New Custom
Built
Applications
In-Memory Processing Engine
SQL Engine Text Engine
Calculation Engine
PAL1
R-Scripts2
Association Analysis
Cluster Analysis
Classification
Analysis
Time Series Analysis
Outlier Detection
Link Prediction
Data Preparation
…
R-Engine

SAP HANA In-Memory Predictive Analytics
Predictive Analysis Library (PAL) – Algorithms Supported
Association Analysis
• Apriori
• Apriori Lite
• FP-Growth
• KORD – Top K Rule Discovery
Classification Analysis
• CART
• C4.5 Decision Tree Analysis
• CHAID Decision Tree Analysis
• K Nearest Neighbour
• Logistic Regression
• Neural Network
• Naïve Bayes
• Support Vector Machine
Regression
• Multiple Linear Regression
• Polynomial Regression
• Exponential Regression
• Bi-Variate Geometric Regression
• Bi-Variate Logarithmic Regression
Probability Distribution
• Distribution Fit
• Cumulative Distribution Function
• Quantile Function
Outlier Detection
• Inter-Quartile Range Test (Tukey’s
Test)
• Variance Test
• Anomaly Detection
Link Prediction
• Common Neighbors
• Jaccard’s Coefficient
• Adamic/Adar
• Katzβ
Data Preparation
• Sampling
- Random Distribution Sampling*
• Binning
• Scaling
• Partitioning
• Principal Component Analysis (PCA)
Statistic Functions
(Univariate)
• Mean, Median, Variance,
Standard Deviation
• Kurtosis
• Skewness
Statistic Functions
(Multi-variate)
• Covariance Matrix
• Pearson Correlations Matrix
• Chi-squared Tests:
- Test of Quality of Fit
- Test of Independence
• F-test (variance equal test)
Other
• Weighted Scores Table
• Substitute Missing Values
Cluster Analysis
• ABC Classification
• DBSCAN
• K-Means
• K-Medoid Clustering
• K-Medians
• Kohonen Self-Organized Maps
• Agglomerate Hierarchical
• Affinity Propagation
Time Series Analysis
• Single Exponential Smoothing
• Double Exponential Smoothing
• Triple Exponential Smoothing
• Forecast Smoothing
• ARIMA
• Brown’s Exponential Smoothing
• Croton Method
• Forecast Accuracy Measure
• Linear Regression with Damped
Trend and Seasonal Adjust

„Predicting My Next Twitter Follower with SAP HANA PAL” by Lucas Sparvieri
http://scn.sap.com/community/developer-center/hana/blog/2013/09/02/predicting-my-next-twitter-follower-with-sap-
hana-pal
*PAL – Predictive Analysis Library

Spatial Processing with SAP HANA
Gain Competitive Advantage by Uncovering New Insights with Native Spatial
Processing
Real-time Spatial
Processing
High-performance algorithms
analyze massive amounts of
spatial data in real time
Mobility Visualization Analytics HTML5 GIS Applications
Spatial Analytics
Optimization
Columnar storage architecture
eliminates need to create spatial
indexes, tessellation, or other
optimization techniques
Geo-content & services
Maps, geo-content, and
geospatial services open
integration for seamless
application development
Spatial Data Types &
Functions
Store, process, manipulate,
share, and retrieve spatial data
directly in the database
SAP HANA
Spatial Processing
Business Data + Spatial Data + Real-time Data
Geo – Services
- Geocoding
- Base maps
Geo – Content
- Political
Boundaries
- POIs
- Roads
Columnar
Spatial
Processing
- Clustering
Calc Model/
Views
- Joins
- Views
Spatial
Functions
- Area
- Distance
- Within
Spatial Data
Types
- Points
- Lines
- Polygons
Transaction
Data
Unstructured
Data
Location
Data
Machine
Data

Examples of some cool ideas from the community
„Experiences with SAP HANA Geo-Spatial Features” by Trinoy Hazarika
http://scn.sap.com/community/developer-center/hana/blog/2014/02/25/experiences-with-sap-hana-geo-spatial-
features-part-1

SAP HANA Text Analytic
 Native full-text and fuzzy search
 Exploit full-text search capabilities for exact, freestyle,
linguistic, fuzzy, and synonym-based search and
ranking
 Info Access Toolkit
 Rapid development of search-enabled applications
through API and reusable UI building blocks
 File Filtering
 Unlock text from binary documents
 Ability to extract and process unstructured text data
from various file formats (txt, html, xml, pdf, doc, ppt,
xls, rtf, msg)
 Load binary, flat, and other documents directly into
HANA for native text search and analysis
 Native Text Analysis
 Give structure to unstructured textual content
 Expose linguistic markup for text mining uses
 Classify entities (people, companies, things, etc.)
 Identify domain facts (sentiments, topics, requests,
etc.)
 Supports up to 31 languages for linguistic mark-up
and extraction dictionary and 11 languages for
predefined core extractions
SAP HANAInformation
Access Services
Suggestion Search Metadata
Column
Store
Tables
Metadata Search Model
Search
Engine
Search
Fuzzy Ranking
Snippets
Text
Processor
Linguistic
Processing
HANA Apps
Applications and Analytics leveraging
Text Search & Text Analysis
capabilities
Search UI configured with
Info Access toolkit running
natively on SAP HANA

„Detecting World Cup GOAL using Twitter and SAP HANA” by Stevanic Artana
http://scn.sap.com/community/developer-center/hana/blog/2014/07/03/goal-detection-using-twitter-and-sap-hana

SAP HANA Graph Engine
• Manage property graphs within flexible, in-memory
columnar store – faster queries and less storage
• Combine graph with advanced analytics – text,
predictive, geospatial – in a single transaction
• Offer GEM language to traverse and manipulate
graphs
• No duplication of data to create graphs
SAP HANA
Graph Engine

http://www.btw-2013.de/proceedings/The%20Graph%20Story%20of%20the%20SAP%20HANA%20Database.pdf

Application
 Leverage remote database’s unique processing capabilities by pushing processing to remote database; monitors and
collects query execution data to further optimize remote query processing
 Compensate missing functionality in remote database with SAP HANA capabilities
 Accelerate application development across various processing models and data forms with common modeling and
development environment
Merge Results
SELECT
from DB(x)
SELECT
from DB(y)
SELECT
from HIVE
Application
One SQL Script
SAP HANA
Virtual Tables
Supported DBs as of SP6: HANA, Sybase ASE, IQ Hadoop/HIVE, Teradata
Data-Type Mapping & Compensate
Missing Functions in DB
Modeling
Environment
Modeling
Environment
Modeling
Environment
Modeling and
Development Environment
Rapid Data Provisioning with Data Virtualization

Examples of some cool ideas from the community
„HADOOP HDFS Explorer built with HANA XS and SAPUI5” by Aron MacDonald
http://scn.sap.com/community/developer-center/hana/blog/2014/07/03/hadoop-hdfs-explorer-built-with-hana-xs-and-
sapui5

SAP HANA with SAP Lumira Server
Applications That Need Easy Ways to Implement Advanced Analytics
 Native – SAP HANA XS application
with Installation using SAP HANA
Lifecycle Manager (LCM)
 Robust with SAP HANA load
balancing, failover, backup, recovery
built-in
 Secure – Identity and access
management based on SAP HANA
platform and users
Lumira Datasets
(real-time or static)
Lumira Stories
SAP
Lumira
SAP HANA
1. Build Lumira Data Sets/Views
(Stored in SAP HANA)
2. Build Story (Stored in SAP HANA)
3. Visualize (uses Lumira Datasets/
Views and Stories stored inside SAP
HANA)
Faster results from real-time transactional data
1 2
3

Top Reasons -> Choose("SAP HANA")
What Do Those Features Mean for You to Choose SAP HANA
Platform?

Storage
Storage
CPU
Memory
CPU
Memory
Sub-Second Response, No Matter How Complex
Process data and application logic in parallel (MPP), using all cores in a multi-core architecture, by effectively partitioning data
Avoid unnecessary compensation (e.g., buffering, data duplication) during application execution by running application using the SAP
HANA application services (built-in web server)
Eliminate disk I/O by keeping all data in memory using column store and by significantly compressing data
Access data faster using any column as index and by accessing only relevant columns via dictionary-encoded column store
CPU
Memory
Bottleneck
Data Hard Disk: 10,000,000ns*/SSD: 200,000ns*
Disk Storage
Log
60ns*
L1 Cache
L2 Cache
L3 Cache
1.5ns*
4ns*
15ns*
Core 1 Core N
Any Column
as Index
Parallelized Query
Query Compressed
Data
Log
Copy into memory
Code
DB App
Data
(DB + App)
SAP HANA
Scan
3.2 billion integers/sec/core
Aggregate
12.5 million integers/sec/core
Ingest
1.5 million records/sec/node

Real-Time Applications, Zero Latency
 Run both transactional and analytical applications on one single data model
– Database tables designed to support simultaneous high volume/high speed transactional and analytical processing
without compromising data consistency (ACID compliance)
 Aggregate on-the-fly with no pre-materialization on key figures, including current transactions, using column store and
parallel aggregation and the optimization for outer joins, distributed joins
 Any delay of availability of transactional data for reporting or analytics has a major impact on business workflow; for
example, period closing. SAP HANA can report (e.g., P&L) while we make adjustments, which is important for the
consolidation.
 The shorter response times enable users to increase the use of the system
Traditional: OLTP and
OLAP Separate
6 Hours
12:00:00 AM
OLTP + OLAP in
SAP HANA
10:00:00 AM 10:00:01 AM
Immediate
Current Data24-hour Old Data
Aggregate
ETL SAP HANA
6:00:00 AM

Embed sentiment fact extraction in same SQL
Embed geospatial in same SQL
Embed fuzzy text search in same SQL
CREATE FULLTEXT INDEX i1 ON
PSA_TRANSACTION( AMOUNT, TRAN_DATE,
POST_DATE, DESCRIPTION, CATEGORY_TEXT )
FUZZY SEARCH INDEX ON SYNC;
SELECT SCORE() AS SCR, * FROM
"SYSTEM"."PSA_TRANSACTION" WHERE
CONTAINS (*, 'Sarvice', fuzzy) ORDER BY
SCR DESC;
Click-
stream
Customer
Data
Connected
Vehicles
Smart
Meter
Point of
Sale
Mobile Structured
Data
Text Data RFIDMachine
Data
Support advanced text analytics
Analyze text in all columns of table and text
inside binary files with advanced text
analytic capabilities such as automatically
detecting 31 languages; fuzzy, linguistic,
synonymous search using SQL.
Structure unstructured data
Use advanced text analytics, such as
sentiment fact extraction, to structure
unstructured data
Analyze streaming data from integrated
ESP in combination with data in HANA
Process geospatial data
Social
Network
SAP
HANA
Any Data
SQL
Geospatial
Data
Process Any Data, in Any Combination, Instantaneously
with SQL

“
It is only a matter of scaling the hardware – there are no other variables or unknowns.
SAP HANA: Re-Thinking Information Processing for Genomic and Medical Data, Prof. Dr. Hasso Plattner, 2013
”
Multi-core/
parallelization
No disk PartitioningDistributed
computing
Scale Up Scale Out
With the power of mathematics and distributed computing, SAP HANA can predictably complete any
information processing tasks, however complex, within a given time-window
• Need new IMC benchmark: introduces new capability, such as
no aggregation or no indices, which needs new benchmark
design
• No pre-aggregated result: The test addresses the load-then-
query ability without using any pre-caching results
Extreme Linear Scalability
Across Multi-Nodes
Query processing time (in seconds)
Query 1
Single customer and
material for one month
Query 2
Range of customers and
material for one month
Query 3
Year-over-Year trending
report for Top 100
customers for 5 years
SALES AND DISTRIBUTION REPORTS
Linear Scalability to Meet Any Time Window

ODBC, JDBC
SAP HANA
 Easily migrate your applications
(e.g., Java, PHP, .NET) using JDBC,
ODBC, and OData/JSON
 Build new web applications with any
open source HTML5/JS libraries,
Server Side JavaScript
 Easy to bring data into HANA
– Import data in CSV, Excel, or
Binary formats. Load Geospatial
files in shapefile, CSV, Binary,
WKT, and WKB file formats.
– Reuse current data sources with
Data Virtualization
– Replicate real-time data from
multiple sources into SAP HANA
for comprehensive data analysis
 Open Cloud Partner Program
allows you to select the best SAP
HANA cloud deployment option from
several partners
App Services
(Web Server)
DB Services
Browser/Mobile
Web JS Lib Data Viz Lib
Web App Server
http(s),OData/JSON
ODBO
Third Party
&
Custom Application
HTTP(S), OData, XML/A
ODBC, JDBC, ADBC, ODBO
MDX, SQL
SQL Script
Any HTML5/JS Library
Stored Procedure
Virtual Tables
Import
Real-time Replication
CSV, Binary, shapefile,
WKT, and WKB files
Bring Your Own Code to an Open Platform

Browser/Mobile
Web App Server
DB Server
SQL
Stored
Procedures
http(s)
Web JS Lib Data Viz Lib+ +
HTML5/JS
Libraries
Browser/Mobile
http(s), OData/JSON http(s)
OLAPPredictiveText Mining
BRM
DB Server DB-oriented Logic
Text Mining
Predictive
SQL Scripts
R Integration
Decision Tables
SAP HANAApp LogicApp LogicApp Logic
App LogicApp LogicApp Logic
Aggregate
+ ++Flexible Table:
 Push-down code: Replace application logic in multiple places with reusable DB logic written in SQL Script, consumed through
OData
 Efficient execution with built-in application services: Significantly improve application performance by running applications using
SAP HANA application services (built-in web server) to avoid multiple layers of buffering and to reduce data transfers and
processing logic
 Optimized and open: Built-in SAPUI5 libraries with open integration to third-party libraries for both desktop and mobile user
experience
 Dynamic Schema: Dynamically add up to 64,000 columns with SQL Insert or Update statements without altering schema
+
App Services
(Web Server)
Procedural App Logic
ODataJava Script
Standard Table:
Transformative Power, Simplified Programming

Apps
SQL Script
(Optimized Query Plan)
Unstructured
PALR-scriptsR Engine
“The HANA platform at Cisco has been used to deliver near real-time insights to our execs, and the integration with R will allow us to
combine the predictive algorithms in R with this near-real-time data from HANA. The net impact is that we will be able to take the
capability, which takes weeks and months to put together, and deliver just in time as the business is changing.
Piyush Bhargava, Distinguished Engineer IT, Cisco Systems (video)
”
“See” the Future Accurately in Real-Time
 Accelerate predictive analysis and scoring with in-database algorithms delivered out-of-the-box. Adapt the models
frequently.
 Execute R commands as part of overall query plan by transferring intermediate DB tables directly to R as vector-oriented
data structures
 Predictive analytics across multiple data types and sources. (e.g., Unstructured Text, Geospatial, Hadoop)
C4.5 decision tree
Weighted score
tables
Regression
KNN classification
K-means ABC classification
Associate analysis:
market basket
Apps
Virtual Tables
OLAP Unstructured
Predictive
Logic
R
Logic
Pre Process Pre Process Pre Process
Geospatial

$
$
$
$
$
$
Web Application Server
Enterprise Search
Business Rule Management
Predictive Analytics
Planning
Geospatial
Data Warehouse Appliance
ETL
Event Processing
Multiple Databases
“Pointing to Glass' Law (sourced to Roger Sessions of ObjectWatch), which states that “for every 25 percent increase in functionality of a
system, there is a 100 percent increase in the complexity of that system,” Gartner emphasizes the ability of an enterprise to get the most
out of IT money spent.
Gartner
”
Text Analytics/Mining/Unstructured Data
Development/Modeling Tools
LifecycleMgmt/Admin/MonitoringTools
 Simplify development, modeling, and administration
environments with Eclipse-based tool
 Reduce TCO: consolidating heterogeneous servers and
data into SAP HANA servers to reduce the TCO for the
system, backups, time for backups, and maintenance
 Avoid hidden costs due to data quality, synchronization,
and latency
 Higher productivity: remove unnecessary tasks to get
significantly higher productivity and help users focus on
working on the material
UnifiedDevelopment/Modeling/
Admin/MonitoringwithEclipse-
basedtool
SAP
HANA
Database Cache
Data Warehouses
De-Layer, De-Clutter. Consolidate!

SELECT Flexible_Choices
FROM SAP.HANA
ORDER BY 1 ASC

SAP HANA Appliance
On-Premise
SAP HANA One (Premium)
Public Cloud
SAP HANA Enterprise Cloud
Managed Private Cloud
Limited Scale Any Scale Elastic Scale
SAP
HANA
SAP
HANA
 Choose hardware (Intel
x86-based architecture)
from hardware vendors
HP, IBM, Fujitsu, Cisco,
Dell, NEC, Hitachi,
Huawei, and VCE as of
July 2013
 Scale as required
 Real-time platform, infrastructure,
and fully managed services from
SAP or from our trusted partners
 Bring your existing licenses to run
all SAP HANA applications
 Mission-critical, global, 24x7
operations
 Start using SAP HANA right away
 Managed by Amazon Web
Services (AWS), Korea
Telecom, Portugal Telekom,
and VMware
 60.5 GB instance size,
allowing for 30 GB of data
 HANA One:
– 99¢ per hour. Pay as you use.
Community Support.
 HANA One Premium:
– USD 75,000 per year including
SAP Enterprise Support
SAP
HANA
Choose and Change Deployment Options Any Time

SAP Cloud powered by SAP HANA
Overview Product Portfolio
Customer Systems
SAP HANA
SAP HANA Enterprise Cloud SAP HANA Cloud Platform Line-of-Business
Apps
(On-Premise) Private Cloud (Managed) Public Cloud
Managed-Cloud-as-a-Service Platform-as-a-Service Software-as-a-Service
People Customer
SAP Business Suite
SAP Business Warehouse
SAP HANA Datamart …
Build Extend Run
applications Finance Supplier
Custom infrastructure and
maintenance
New
Apps
Collaboration
People
SAP JamSoccer
Health
Consumer
Startups
Business
Ariba
Commerce
Hybris
Any
DB
Integration
leads to new and innovative business processes

SAP HANA Delivers Results for Business Today
1,700+ startups
from 57 countries building
applications on SAP HANA
509% ROI from
building new application
at University of Kentucky
Forrester reports 37%
cost savings for applications
running a single system for
OLAP and OLTP
Simple financial
application reduces data
footprint by up to 37x
3,000 software & tech
partners; 4,000
service partners
200+ Custom-built
applications or PoCs
running on SAP HANA
platform

SAP Startups Focus
http://startups.saphana.com

Endless Possibilities
Build Real-Time Modern Applications to Transform Your Business
Ad hoc
Reporting
Application
Dynamically
aggregate data at
any granularity
without pre-
configuration
Planning &
Optimization
Application
MONTH
S MT W T F S
Run real-time
planning or
optimization to find
the best solutions
Hybrid Data
Analytic
Application
change
Course
seminar
learn
evaluation
knowledge
discussion
creativity
scale
developlearner
critique
Process or analyze
multiple types of
data, such as
geospatial, text, or
graph data
Internet-of-Things
Application
Network-embedded
devices or sensors to
connect and change
the world
Predictive
Application
Predict the future
based on deep
analysis of history
data
Database Services
SAP HANA Platform

SAP HANA In-Memory Platform
Ideal Platform for Next-Generation “Smart” Applications
 HTTP(S), OData,
XML/A
 ODBC, JDBC,
ODBO
 SQL, MDX
Easier
Consumption:
Easier
Development:
 JavaScript, HTML5
 Connect any
programming
language
 App/web services
 Decision table
Easier
Processing:
 NLP, Predictive,
R-Integration
 Spatial processing,
ad hoc OLAP views
 Data virtualization
Easier
Ingestion:
 Replication,
streaming,
ETL/ELT
 Integration,
data cleansing
Personalized
recommendation with
machine learning,
predictive, and rules
Natural
language
processing
Process any variety/
volume (e.g.,
unstructured)
Respond within
predictable time
windows
Key capabilities required for next-generation “Smart” applications:
SAP HANA is a high-speed processing platform to enable:

Learn
 SAP HANA Academy
 SAP Open Courses
 SAP Developer Network
 SAP App Development Partner Center
Try
 SAP HANA Developer Edition
 SAP HANA Cloud Platform
 SAP Idea Incubator
 SAP HANA One
Experience
 SAP HANA Customer Stories
 SAP HANA Use Case Map
 SAP Customer Journey iPad App
 SAP HANA Use Case Repository
Where to Find More Information

57© 2015 SAP SE or an SAP affiliate company. All rights reserved.
Open
Leverage existing investments with an open platform
6
Speed
Sub-second response, no matter how complex
1
Real-Time
Real-time applications, zero latency
2
Any Data
Process any data, in any combination, instantaneously
with SQL
3
Any Source
Rapid data provisioning with data virtualization
4
Consolidation
De-layer, de-clutter. Consolidate!
9
Simplicity
Transformative power, simplified programming
7
Prediction
“See” the future accurately in real time
8
Predictable Completion
Linear scalability to meet any time window
5
Choice
Choose and change deployment options any time
10

© 2015 SAP SE or an SAP affiliate company. All rights reserved.
Thank("you")!
Vitaliy Rudnytskiy
SAP Developer Center
http://developers.sap.com
http://twitter.com/sygyzmundovych
http://scn.sap.com/people/vitaliy.rudnytskiy
http://about.me/witalij

© 2015 SAP SE or an SAP affiliate company. All rights
reserved.
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National product specifications may vary.
These materials are provided by SAP SE or an SAP affiliate company for informational purposes only, without representation or warranty of any kind, and
SAP SE or its affiliated companies shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP SE or SAP affiliate
company products and
services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be
construed as constituting an additional warranty.
In particular, SAP SE or its affiliated companies have 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 SE’s or its affiliated companies’ strategy and possible
future developments, products, and/or platform directions and functionality are all subject to change and may be changed by SAP SE or its affiliated
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Developing and Deploying Applications on the SAP HANA Platform

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