SAP HANA Update

Saul Cunningham SAP Big Data Centre of Excellence

ERP + LOB

Systems of Record

Data “In”

The first 35 years: innovated with ERP & LOB apps

ERP + LOB

Systems of Record

Data “In” Business

Analytics Systems of Engagement

Info “Out”

Five years ago: innovated with analytics

ERP + LOB

Systems of Record

Data “In” Business

Analytics Systems of Engagement

Info “Out”

Mobility Accessible Systems

Two years ago: innovated with mobility

ERP + LOB

Systems of Record

Data “In” Business

Analytics Systems of Engagement

Info “Out”

Mobility Accessible Systems

Oracle DB2 SQL Other

Business Applications Performance Bound by

Data

Oracle SQL

DB2, etc.

Now: innovating with the database

ERP + LOB

Systems of Record

Data “In” Business

Analytics Systems of Engagement

Info “Out”

Mobility Accessible Systems

Oracle Other ELT or ETL HANA

In Memory Database

ELT or ETL Oracle

SQL

DB2, etc.

HANA In Memory Database

HANA accelerates data, apps and analytics

ERP + LOB

Systems of Record

Data “In” Business

Analytics Systems of Engagement

Info “Out”

Mobility Accessible Systems

HANA In Memory Database

Long term: HANA is the database

A common Database Approach for OLTP and OLAP

Using an In-Memory Column Database Hasso Plattner

Transact Analyze Accelerate Transactions + Analysis

directly in-memory

VS

HANA = HAsso’s New Architecure

HW technology innovations

64 bit address space – 2 TB in

current servers

100 GB/s data throughput

Dramatic decline in

price/performance

Multicore architecture (8 x 8 core 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

SAP SW technology innovations

Convergence of improved hardware economics and technology innovations enables SAP to deliver on its

vision of the real-time enterprise with in-memory business applications

Leverage new innovations

HANA In-Memory Vision – realised to market in June 2011

Natively In-Memory | Massively Parallel | OLTP + OLAP | Structured + Unstructured | Legacy + New

3B Scans/s /core | 12.5M aggregates /s /core | 1.5M inserts/s

SCALE TO MEET YOUR NEEDS

Intel Optimised Hardware Applicance

Next Generation Open Appliance | Developed with Intel

IBM | HP | Cisco | VCE | Fujistu | Dell | Hitachi | Lenovo

Non-SAP & SAP systems | Supports Open Standards

Lower Power Usage | Lower TCO | Lower Failure Rate

Grow incrementally

Start small | Grow as required

Scale Up or Scale Out | Data Centre Ready

Cloud Ready

Data Centre Ready

Fault tolerance | Disaster Recovery | High Availability

In machine persistence| Storage replication | System replication

Auto-services restart| Auto-node failover

True real time analytics

No latency between transaction & analytics

Data logically modeled on the fly | No aggregations | No materialised views | No nightly batch jobs

Drastically simplifies data development landscape | Greater agility for the business

1 PB Performance Benchmark Largest in-memory system in the world

(see the 1PB benchmark whitepaper blog at saphana.com)

100 Nodes, 100 TB in DRAM | 10 Years of SD Data | 1.2 T Rows (330 Million transactions / day)

Ad-hoc Simple Queries (e.g. Month Report: 430ms – 647ms | Drill-down: 142ms Complex Queries (e.g. YoY report): 1.2s - 3.1s

Query Throughput (Queries per Hour): 7,547 for 1 stream | 57,202 for 10 streams | 112,602 for 60 streams

Breakthrough Transactional Performance

Insert: 1.5M Records/sec

COLUMN BUFFER ROW BUFFER COLUMN STORE Column store as transaction database | Foundation for

SAP Business Suite

Single copy of the data | Real real-time!

Maximising the Boundaries of all 5 Dimensions of Data...

Going Deep { complex questions, interactive questions, multi-dimensional

And Broad { large amounts of data, many types of data, all necessary data

In Real-time { recent data, real-time data

ASAP { fast response, interaction within the window of opportunity

With Agility { no data prep, no-pre-aggregates , no-tuning

Renewal Everywhere

2013 & Beyond Legacy + New – Without compromise

2012 HANA Platform (Developers, Startups, 10K/100K, New Frontiers) Business One, Planning, CRM & others on HANA

2011 HANA for Analytics (BOBJ, BW and other) HANA GA

2010 & Prior Designing & building HANA

1042 Customers | > 500 live | 19 in 10K Club

100K Club Winners

Yodabashi

NonFu Spring Co.

Mitsui Knowledge Co.

Club 10k

Essar

SAP IT

Cornell University

Charmer Sunbelt Beverages

Provimi

Emirates Airlines

Haier

Fastest growing product in SAP history

TCO lowered

Data Search Discovery & Analysis

Data Itself guides the process| triggers further questions

Big data | Search driven| Mashable

Next generation visualizations | Cloud | On-Premise

Discover | Search | Explore | Share

SAP Mobile Analytics

Targeted & Personalized | Always Accessible | Collaborative

Augmented experience | Geo Spatially Savvy | Real-time Platform & Targeted Apps

Leverage existing BI platform | Optimized for Big data

Author Once | Multiple Platforms |Securely Managed | Easily deployed

Big Queries, Big Data & Quality Data

Unstructured data frontier | Linking EDW & Hadoop is essential

Hadoop |Cost Efficient to Store & Process| Scalable

In-Memory computing | High Value Data | User Driven | Federate SAP HANA & Hadoop via SAP BI & EIM

Predictive Analysis & Big Data

Increased Business Interest | Increased Data Value |Increasing Technology Performance

Empower the Business |In-time insights | Context Driven

R-Integration | In-Built PAL in HANA|In-house developed algorithms

Next Generation Real-Time Applications

Real-time operational analytics | non-disruptive | Cloud or On-Premise

Applications Powered by HANA | Line of Business | Solutions for Industry (e.g. Telco, Utilities, Banking) |

Cross Industry

Platform for Enterprise | Central Master Data Hub | CRM 360 | Business Suite on HANA | Cloud or On-

Premise

The SAP HANA real-time data platform is for next generation applications & businesses

Analytical | Data Warehouses | Transactional

Speed is key | Develop| Integrate| Analyze | Decide

SAP Real Time Data Platform

Specialist in genome research

Want to enabled cancer treatment optimised to patients DNA

Research shows that your DNA anomalies you will respond to certain drugs and therapies better than

others

41% of us will be diagnosed with cancer at some point in our lives…

Case Study – Mitsui Knowledge Industry

Vision is possible as DNA sequencing costs have fallen dramatically

Soon cost will be under $1000 and be completed in less than a day

Challenge is now to reduce the time to analyze the genome sequence

Case Study – Mitsui Knowledge Industry

Data analysis for sequenced genome 3 step process taking 2-3 days | Aim to get as fast as

possible

Preprocess

- Alignment of patient’s DNA sequence with a “normal” sequence

Data analysis

- Complex comparison of patients DNA identified against 10’s of millions of preprocessed sequences to identify mutations/variants

Actions

- List of actionable mutated genes and related medicines

- Create predictive model (prognosis, driver mutation, etc.)

Case Study – Mitsui Knowledge Industry

Hadoop used to preprocess the DNA sequence

HANA used to analyze the genome sequence

R used to in predictive modeling of treatments

“Genomic DNA analysis in real-time will transform how we enable comprehensive patient care to fight against cancer. SAP HANA will be the mission

critical and reliable data platform to make real-time cancer analytics into a reality. Separately, our internal technical comparison demonstrated that SAP

HANA outperforms a traditional disk-based system by factor of 408,000 when performing other types of data analysis.”

Yukihisa Kato, Director & Executive Officer, CTO, Research and Development Center, MITSUI KNOWLEDGE INDUSTRY CO.,LTD.

“ ”

Case Study – Mitsui Knowledge Industry

More information

http://www.saphana.com/

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

https://experience.sap.com/

Saul Cunningham

Big Data Centre of Excellence

SAP Australia

Tel: +61 417 495 010

Email: saul.cunningham@sap.com

Backup slides

HANA High Availability – Disaster Tolerance Cluster across Data Centers incl. mount management

HANA HA-API supports the remount process

and tells OS/hardware partner tools to offer the

right file systems at the right node.

HA & DR Details

Solution Supported Downtime Scenarios Detect RPO RTO Ramp Failback

System

Replication

Business continuity for planned downtime, software

fault, host crash or disaster Manual 0 1-2 mins seconds Manual

Storage

Replication

Business resumption when disaster;

recovery from local storage corruption Manual 0 hours-days mins-hours Manual

Persistence Restart from software fault, power outage

or host crash Auto 0 mins mins-hours Auto

Backups Recovery from storage or data corruption,

operator error, host crash, or disaster Manual large hours-days mins-hours Auto

Host Auto

Failover

Automatic recovery from software fault

or host crash Auto 0 ~20 mins mins-hours Auto

Service Auto

Restart Automatic recovery from software fault Auto 0 ~5 mins mins-hours Auto