The document discusses in-memory computing with SAP HANA, highlighting its role in addressing challenges posed by hyperconnectivity and rising customer expectations. It emphasizes the importance of real-time data processing for improving customer experience and business operations. Additionally, it details the features of the SAP HANA platform, including its ability to run transactions and analytics together, advanced data processing capabilities, and various deployment options.

1. In-memory computing
with SAP HANA
June 2015
Amit Satoor, SAP
@asatoor
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 1

2. Hyperconnectivity across people, business, and devices give
rise to a new digital economy powered by real-time data
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 2
75 billion connected devices
in the Internet of Things
Over 2.55 billion
social media users by 2020
U.S.$65 trillion in global trade
through connected businesses
Source: SAP Corporate Fact Sheet 1/2015Source: www.emarketer.comSource: Business Insider

3. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 3
As five billion people reach middle class, new challenges arise in
customer expectations, workforce, and resource management
Dramatically Changing Workforce
82% customers
stop doing business
with a company due
to a poor experience
$5.6T savings through
connected vehicles
67% increase in crop yields
22% increase in supply
chain efficiency
Rising Customer Expectations
71% of business leaders
believe that customer
experience is the next
battleground
High employee
engagement: 3x higher
operating margin
72% of Millennials feel their
current organization is not
making full use of their skills
Pressure on Resources
Water 1.5x by 2030
Energy 1.5x by 2020
Food 1.5x by 2030
Metals 2x by 2030
Sources: Impact Report, Harris Interactive. Colin Shaw and John Ivens, 2010; Deloitte Millennial Study, 2015; Shell, 2014; WRI, 2014; SAP SE, 2014. Towers Watson, 2012

4. 77% of CEOs are creating value in the customer experience
with digital technologies
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 4
Mobile Social Big Data
Cloud
36% of all data
will be stored in the cloud by 2016
90% of the world's population
over 6 years old
will have a mobile device by 2020
75% of customers rely on
social media to
influence their purchasing decisions
44 trillion gigabytes of data
generated by 2020
Sources: McKinsey Study, 2013; CloudTweaks.com; Ericsson, 2014; CIO Insight, 2014; Adweek, 2014

5. A breakthrough in today’s information processing architecture is
needed
DEEP
Complex & interactive questions
on granular data
BROAD
Big data,
many data types
HIGH SPEED
Fast response-time,
interactivity
SIMPLE
No data preparation,
no pre-aggregates,
no tuning
DEEP
Complex & interactive questions
on granular data
SIMPLE
No data preparation,
no pre-aggregates,
no tuning
REAL -TIME
Recent data, preferably real-time
HIGH SPEED
Fast response-time,
interactivity
OR
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 5

6. 10.2% or U.S.$237 billion of profits are lost by the top
200 global companies due to hidden costs of complexity
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 6
Source: The Simplicity Index 2011, 2015 Wharton-SAP Run Simple Survey.
Real-time
Business
Scenario Real-time bonus
calculations for
consumers
Sales
Customer
Service
Customer overdue credit
calculation by product areas
Finance and
Operations
Iterative period end closing
with new posting into
accounts constantly
Manufacturing
New ATP strategies; MRP run
for individual ATP
check/instant re-planning
IMPACT ON BUSINESS Slow Response Times | Usability Challenges | Lack Of Adaptability
IMPACT ON IT High Latency | Complexity | High Cost of Solutions
Transactional
Datastore
Data
Warehouse
Sensors
Data
Mobile
Data
Archives Social & Text Geo-Spatial
Location
Intelligence
Order
Processing
Operational
Reporting
Real-time Risk
& Fraud
Trend
Analysis
Sentiment
Analytics
Predictive
Analytics
Pattern
Recognition
Analyze
ETL
Staging
Collect
Clean-Data
Quality
Transact
Aggregate
Summarize
Communicate
Monitor
Predict
Planning
0
1

7. CPU
Next-generation Software & Hardware Architecture
Removing data processing bottlenecks using latest innovations in
computing
STORAGE
MEMORY
Compression
PartitioningOLTP+OLAP
in column Store
Insert Only on Delta
No Aggregate tables
(Dynamic Aggregation)
Solid State Flash HDD
64bit address space
1 TB in current servers
Dramatic decline in price/performance
L3
Cache
L3
Cache
L3
Cache
L3
Cache
L3
Cache
L3
Cache
L3
Cache
L3
Cache
Multi-Core Architecture
8 CPU x 10 Cores per blade
Massive parallel scaling with many blades
Logging and Backup
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 7

8. SAP HANA Platform - The in-memory computing platform for
all Applications
SAP HANA Platform
Application Services
Database Services
Integration Services
SAP, ISV and Custom Applications
All Devices
OLTP + OLAPONE open platform ONE copy of the data
All Data
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 8

9. Standard-based and Open
• Database Services
– Standard RDBMS
– ACID, SQL 92 Compliant
– Accessible thru JDBC, ODBC, JSON, OData
– Standard security model
– Choice of third party administration tools
• Application Services
– Choice of application servers and
webservers
– Eclipse based and web development tool
– Include web server with Java Script support
– Include HTML5 UI libraries
• Integrations Services
– Data movement and federation with
existing DBs
– Integration with R and Hadoop
SAP HANA Platform
Application Services
Database Services
Integration Services
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 9

10. SAP HANA Platform
Application Services
Integration Services
Database Services – Foundation and Processing Capabilities
In-memory Database Services
 Turns data into real-time information
 No database tuning required for complex and ad hoc queries
 Run Transactions and Analytics together on one system and one copy of data
 Ready for Cloud, Hybrid, or On-premise deployment
 Not limited by the size of memory
Advanced Compression
Multitenant Database Containers
In-Memory ACID Columnar
Dynamic Tiering
Multi-Core / Parallelization
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 10

11. Comprehensive advanced data processing and analytics
SAP HANA Platform
Application Services
Integration Services
Database Services – Foundation and Processing Capabilities
Predictive
Search
Function Libraries
Spatial
Text MiningText Analytics
Graph
Data Quality
 Run applications with dramatically different datatype characteristics in the same system
 Optimize graph, planning, and rules applications on the same data
 Empower your business via built-in predictive analytics, business functions, and data quality
Series Data
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 11

12. Application Services- Web server and database in one system
reducing data movements
Database Services
SAP HANA Platform
Application Services
Integration Services
J/ODBCADO.NET ODataJSONSQL HTML5 MDX XML/A
 Deliver consumer-grade User Experiences for any device, automatically
 Support for open development standards – HTML5, JSON, Java Script
 Built-in tools to develop, version-control, bundle, transport, and install applications
Web Server SAP Fiori UX
Application Lifecycle
Management

13. Integration Services - Data from any source for a complete
view of the business
SAP HANA Platform
Integration Services
Database Services
IBM DB2, Oracle, MS SQL
Server, Twitter, HIVE,
OData, Custom Adapters
IBM DB2, Netezza,
Oracle, MS SQL Server,
Teradata, SAP HANA,
SAP ASE, SAP IQ, HIVE
Application Services
Loading
 Access information stored in data silos while keeping the data in place
 Replicate and move any type of data in real-time to the cloud and on-premise when necessary
 Capture and analyze live data streams and route to appropriate storage or dashboard
 Multiple access points from HANA to Hadoop data: thru Spark, Hive, HDFS and Map Reduce
functions
Federation
Smart Data Access
Smart Data
Integration
Hadoop Integration
Smart Data Streaming
(CEP)
Streaming
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 13

14. J/ODBCADO.NET ODataJSONSQL HTML5 MDX XML/A
Comprehensive services with in-memory computing to make
information available to any application
Smart Data Quality Series Data Functional Libraries
Smart Data Integration Smart Data Streaming
Graph* Planning**Text AnalyticsSearchSpatial Predictive
SAP HANA Platform
Application Services
Web Server | JavaScript | Fiori UX | Application Lifecycle Management
Integration Services
Database Services
OLTP + OLAP | Data Modeling | Stored Procedures | Multitenant Database Containers | Dynamic Tiering
Smart Data Access
| | |
||
| |
||
On-Premise | Cloud | Hybrid
* Graph is in controlled availability
** Not available for external use. Available with SAP products – SAP Business Warehouse powered by HANA, Business Planning & Consolidation(BPC), Sales & Operations Planning
(S&OP).
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 14

15. Node nNode 2Node 1
Choose the right on premise deployment option
Appliance
All in one box by certified partners
Tailored Data Center
Integration
Choice of components that meet SAP
requirements from different vendors
SAP HANA System
Software
Server
Network
Storage
Software
Server
Network
Storage
Software
Server
Network
Storage
Node n
SAP HANA System
Node 2Node 1
Software
Server
Network
Storage
Software
Server
Network
Storage
Software
Server
Network
Storage
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 15

16. High Availability (HA) and Disaster Recovery (DR)
Ensuring the most demanding service-levels
Host Auto-Failover (HA)
 Within one scale-out system
 N active nodes, M standby node(s)
 Automatically switch to standby node
System Replication (HA & DR)
 Across multiple systems / locations
 Continuous data transfer from memory
 Fast switch-over on system failure
Geo clusters
Metro cluster
Sync
Async
Async
Storage
SAP HANA
(Primary)
Node
Storage
SAP HANA
(Secondary)
Node
Storage Replication (DR)
 Across multiple systems / locations
 Transfer data using storage mirroring
 Low cost option
Supports campus, metro and geo clusters with multiple hot standbys
Campus
cluster
SAP HANA
Node 1 Node 2 Standby
Storage Storage
SAP HANA
(Primary)
Node
Storage
SAP HANA
(Secondary)
Node
Secondary system can be used for Dev/QA.
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 16

17. SAP HANA Platform
All SAP applications run better with in-memory computing
Core Business
Processes
S/4HANA
Data Warehouse
and Data Marts
BW on HANA
Advanced
Analytics
BPC, S&OP, CO-PA
Operational
Reporting, BI
HANA Live, Lumira
Cloud Solutions
Successfactors,
Sales, Service and
Marketing
Business
Network
Ariba
Big Data
Customer
Engagement
Intelligence
IoT
Predictive
Maintenance
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 17

18. Common use cases
Optimizing Business
Operations
Operational Reports,
Dashboards, and Analytics
Real-time Operational Intelligence
Data Warehouse and
Data Mart
Big Data
Decision Support, Simulation
and Automation
Get instant insights into real-
time transactions to optimize
business operations
Analyze and visualize
operational details to support
your day-to-day activities
Run queries against operational
data, streams and events to deliver
real-time insights
Deliver actionable insights on
enterprise-wide or
departmental data
Uncover the value in large,
complex and rapidly growing
data sets
Streamline and automate
business processes with
advanced analytics
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 18

19. Deliver results for business today
5,800+
SAP HANA customers
1,850+ SAP Business Suite and
1,600+ BW powered by SAP HANA
customers
1,800+ startups from 57
countries innovating on SAP HANA
10,000 times faster reports
37+ SAP HANA Cloud Data Centers
Worldwide
(from SAP and IBM)
Forrester reports 37%
cost savings using a single
system for Analytics and
Transactions
© 2015 SAP SE or an SAP affiliate company. All rights reserved. 19

20. Run Simple.
Thank you.