SAP HANA. Jake Klein/ SVP SAP HANA June, 2013

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1 SAP HANA Jake Klein/ SVP SAP HANA June, 2013

2 SAP 3 YEARS AGO Middleware BI / Analytics Core ERP + Suite

3 2013 WHERE ARE WE NOW? Cloud Mobile Applications SAP HANA Analytics D&T

Changed Reality Disruptive Performance 4 CPU w/ 10 cores each (optional 8CPU ->

5 Programming for a New Platform CPU Core CPU Cache Main Memory Disk Performance bottleneck today: CPU waiting for data to be loaded from memory into cache Performance bottleneck in the past: Disk I/O 2012 SAP AG. All rights reserved. 7

12 Moore s Law: CPUs core 32 bits 4MB 2 cores 2 CPUs per server External Controllers 8 Sockets X 10 Cores 160 threads per server On-chip memory control Quick interconnect VM and vector support 64 bits; 256 GB - 1 TB More cores, bigger caches 480 Threads per server Greater on-chip integration (PCIe, network,...) Data-direct I/O Tens - hundreds of TBs 2012 SAP AG. All rights reserved. Images: Intel, Danilo Rizzuti / FreeDigitalPhotos.net 16

13 In-memory computing SAP HANA HW technology innovations Multicore architecture (8 x 10 core CPU per blade) Massive parallel scaling with many blades One blade ~$50,000 = 1 enterprise class server SAP SW technology innovations Row and column store Compression Partitioning 64 bit address space 2 TB in current servers 100 GB/s data throughput Dramatic decline in price/performance No aggregate tables Insert only on delta 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 2012 SAP AG. All rights reserved. 17

14 Operational Reporting Oil and Gas We use about 140,000 different materials, which creates several million records per year which have to be analyzed to determine which materials should go to which locations. The possibility to work directly with operational data in a real time mode with large volumes of our data is a tremendous opportunity. CIO, Oil and Gas Company 16 hours before HANA 2 minutes with HANA (HANA processing time 3 sec) 2012 SAP AG. All rights reserved. 18

15 ERP Accelerator - CPG Prior to SAP HANA, we were unable to run full analytics in a reasonable timeframe. With SAP HANA, we will be able to run analytics at a local level on specific brands and locations, and at the lowest level of detail in real time. CIO, CPG Company 4 hours before SAP HANA few seconds with SAP HANA 2012 SAP AG. All rights reserved. 19

16 Suite On HANA Customer Experience SAP CO/PA Accelerator ERP w/o HANA ERP with HANA Acceleration factor vs. ERP EBIT with commodity sales initial report EBIT with commodity sales drilldown by alphacode Cost allocation initial report Cost allocation drilldown by sending cost center 280 sec 7 sec (DB 2,8 sec)* 620 sec 5 sec (DB 2,9 sec)* 45 sec 5 sec (DB 3,4 sec)* 260 sec 7 sec (DB 3,3 sec)* Additional drilldowns are now possible e.g. by customer and article (not feasible before) Drilldown performance not dependent on availability of suitable aggregation level, selection always on line item level from In-Memory Database Existing ERP reports are accelerated with no changes to report definitions *DB measurements show the selection runtime on HANA. Non-DB time is likely to decrease if the application server runs on production hardware SAP AG. All rights reserved. 20

17 THE HANA EFFECT Customers 30 in 10K Club +700 on HANA ONE 25 Verticals 69 Solutions 483 startups 9 HW Vendors Transactions Analytics NLP Text Search & Analysis GIS PAL XS Hadoop 2B /sec /core 10M /sec /core 1M /sec

SAP HANA Software Component View SQL SQL Script MDX

Application Function Libraries Business Function

extensions Parallel Calculation engine Parallel data

Columnar Object Graph Store Multiple in-memory stores

18 SAP HANA Software Component View SQL SQL Script MDX Other Analytical and special interfaces Text Analytics Application Function Libraries Business Function Library Predictive Analysis Library Application logic extensions Parallel Calculation engine Parallel data flow computing model Relational Stores Row based Columnar Object Graph Store Multiple in-memory stores Managed Appliance Appliance packaging 2012 SAP AG. All rights reserved. 22

19 The Five Dimensions of HANA Applications Dimension Complex Questions Large, Multi-type data Recent Data Interactive Full, Raw Data Expectations of Technology Programmatic ability to go Deep, apply complex analytics, predictive and statistical techniques Ability to go Broad, combine structured and text search on massive amounts of data Real Time Computing and response High Performance No pre-fabrication, aggregation, tuning If you need three out of five it is an excellent fit for HANA If you need all five - only HANA can support you!! 2012 SAP AG. All rights reserved. 24

21 Thank you

SAP HANA Scalability. SAP HANA Development Team

SAP HANA Scalability. SAP HANA Development Team SAP HANA Scalability Design for scalability is a core SAP HANA principle. This paper explores the principles of SAP HANA s scalability, and its support for the increasing demands of data-intensive workloads.