SAP DB2 V10.5 mit BLU Acceleration Die neue IBM In-Memory Technologie eröffnet neue Möglichkeiten für Ihr Business

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1 SAP DB2 V10.5 mit BLU Acceleration Die neue IBM In-Memory Technologie eröffnet neue Möglichkeiten für Ihr Business

2 SAP auf DB2 Entwicklungs-Team SAP - DB2 Development Entwicklung von SAP Code Entwicklung von DB2 Code für SAP-spezifische Funktionen SAP Development Support Zusammenarbeit mit DB2 Service Gemeinsames IBM and SAP Team SAP - DB2 Integration Center Integration von neuem DB2 Code mit existierenden SAP Releases DB2 QA für jeden neuen DB2 code level mit SAP Anwendungen weit vor IBM GA SAP Development Support Zusammenarbeit mit DB2 Service Gemeinsames ibm und SAP Team

3 SAP auf DB2 ist ein vollständig integriertes Produkt SAP auf DB2 ist ein voll integriertes Produkt Integrierte Installation der DB2 Software mit SAP install * Integrierter Hochverfügbarkeits Setup mit SAP install * One-step SAP-DB2 Konfiguration: DB2_WORKLOAD=SAP Komplette DB2 Administration und Monitoring mit SAP DBA Cockpit One-stop Support Alle Kunden erhalten "One-stop Support" durch SAP nur ein einziger Kontakt Gemeinsames IBM und SAP Support Team Synchronisierte Wartungszyklen IBM DB2 folgt der SAP 7+2 Wartungsstrategie *as of SAP NetWeaver 7.0 SR3 and SAP Applications based on NW 7.0 SR3

4 DB2 Optimiert für SAP - Roadmap

5 Eine Auswahl der SAP on DB2 Technology Highlights

6 DB2 Optimierungen für SAP COPA und andere SAP Anwendungen SAP COPA Profitabilitäts-Kalkulation Komplexe SQL Queries mit grosser Zahl aggregierter Zeilen (ähnlich zu BW) Kandidat für Column-store und In-memory Technologie COPA: Nutzung DB Parallel Processing (ohne BLU) GLEICHE Hardware!!! DB2 parallel degree: 1 -> 8 bis zu 4x schneller DB2 parallel degree: 1 -> 16 bis zu 7x schneller COPA: Resulte mit DB2 9.7 GLEICHE Hardware!!! bis zu 3.8x schneller mit DB2 parallel processing im Schnitt 1.8x schneller mit DB2 parallel processing hours 12,00 10,00 8,00 6,00 4,00 2,00 0,00 SAP COPA Profitability Calculation Without parallel processing, run time (h) With parallel processing, run time (h) 2.7 Average 1.5 Average SAP Bank Analyzer / SAP Retail Study on Horizontal Scalability of a Typical SAP Bank Analyzer Scenario on IBM DB purescale and POWER7 ( SAP Enterprise Data Warehouse for Point of Sales Data Optimized for IBM DB2 for Linux, UNIX, and Windows on IBM Power Systems ( 6

7 DB2 Nearline-Storage für SAP-BW niedrigere Kosten, bessere Online- Performance Separate SAP BW Online Daten und Near-Line Storage (NLS) Daten Vollkommen transparent für SAP BW Anwendung keine Änderung der Anwendung notwendig! Kleine, schnelle Online Datenbank für häufig genutzte Daten Grosse (und langsamere) Near- Line Datenbank für archivierte Daten DB2 Alleinstellungsmerkmal SAP NetWeaver BW DB Interface DBMS Layer Relational DB Interface SAP- BW Online Database high performance storage Transparent Access BI OLAP BW OLAP BI Data Manager General General Near-Line NLS Interface Near-Line TREX NLS / Partner DB2 LUW Interface Near-Line DB2 Database low cost storage 7

8 DB Optimiert für SAP Anwendungen Höchste Performance & niedrige Kosten Verfügbarkeit DB ist seit Juni 2013 verfügbar DB für SAP ist seit August 2013 verfügbar DB für SAP mit BLU Acceleration erwartet bis Ende 2013 Lizenz OEM: BLU wird Bestandteil der SAP DB2 ASL Lizenz sobald zertifiziert Direkt: DB2 Advanced Enterprise Server Edition beinhaltet BLU (ohne zusätzliche Kosten) "IBM is working closely with SAP to certify DB in similar time frame as previous major releases. This usually occurs about 8 weeks, give or take, after we GA, so, assume late August for the certification statement from SAP. As with any release, this includes evaluation and exploitation of all features in this release where appropriate (including BLU acceleration). We would be happy to help arrange and participate in a joint meeting/call with you, SAP and IBM to discuss SAP's plans further. - Torsten Ziegler, Development Manager SAP DB2 porting Team, SAP

9 BLU Acceleration Eine neue Generation von Daten-Management Innovationen 8-25x schneller bei Reports und Analysen 1 bis zu 1000x schneller bei manchen Queries 2 10x Storageeinsparung 3 Nahtlos integriert in neue DB2 Version 10.5 für einfache out of the box Nutzung auf bestehender Infrastruktur BLU Acceleration 1 Based on internal IBM testing of sample analytic workloads comparing queries accessing row-based tables on DB vs. columnar tables on DB Performance improvement figures are cumulative of all queries in the workload. Individual results will vary depending on individual workloads, configurations and conditions. 2 Based on internal IBM tests of pure analytic workloads comparing queries accessing row-based tables on DB vs. columnar tables on DB Results not typical. Individual results will vary depending on individual workloads, configurations and conditions, including size and content of the table, and number of elements being queried from a given table. 3 Client-reported testing results in DB early release program. Individual results will vary depending on individual workloads, configurations and conditions, including table size and content.

10 Warum ist BLU Acceleration einzigartig? Unerreichte IBM Forschungs- und Entwicklungs-Innovationen Dynamic In-Memory Spaltenorientierte In-Memory Verarbeitung mit dynamischer Auslagerung nicht genutzter Daten auf Storage C1 C2 C3 C4 C5 C6 C7 C8 Actionable Compression Einzigarte Datenkomprimierung mit Beibehaltung der Sortierreihenfolge ermöglicht Nutzung der Daten ohne Dekomprimierung Encoded Instructions Data Parallel Vector Processing Multi-core und SIMD Parallelverarbeitung (Single Instruction Multiple Data) Results Data Skipping Irrelevante Daten werden bei der Verarbeitung übersprungen Super Fast, Super Easy Create, Load and Go! Keine Indices, keine Aggregate, Kein Tuning, Keine SQL- oder Schema-Änderungen

11 BLU Acceleration Illustration 10TB Query in Sekunden oder schneller Das System: 32 cores, 1TB memory, 10TB Tabelle mit 100 Spalten und Daten über 10 Jahre Die Query: Wie viele Abschlüsse hatten wir in 2010? SELECT COUNT(*) from MYTABLE where YEAR = 2010 Das Ergebnis: In Sekunden oder weniger weil jede CPU nur 8 MB Daten untersuchen muss 10TB data Actionable Compression reduziert Daten auf 1TB In-memory Column Processing reduziert zu 10GB Data Skipping Reduziert zu 1GB Parallel Processing 32MB linearer Scan auf jedem Core via Vector Processing Scan so schnell wie bei 8MB durch SIMD Ergebnis in Sekunden oder weniger 11

12 DB2 BLU - Seamless Integration into DB2 Built seamlessly into DB2 integration and coexistence Column-organized tables can coexist with existing, traditional tables Same schema, same storage, same memory Same SQL, language interfaces, and administration Column-organized tables or combinations of column-organized and row-organized tables can be accessed within the same SQL statement Dramatic simplification Just Load and Go Faster deployment Fewer database objects required to achieve same outcome Requires less ongoing management Due to its optimized query processing and fewer database objects required Simple migration Conversion from traditional row table to BLU Acceleration is easy Users only notice speed-ups; DBAs only notice less work!

13 DB2 BLU Integration into SAP BW Integration into SAP BW Workbench SAP ABAP Dictionary extension to support BLU tables as new table type BLU conversion of existing BW objects DBA Cockpit: Support of new performance metrics for BLU tables Configuration for BLU feature is fully compatible with SAP settings - DB2_WORKLOAD=SAP 13

14 DB2 BLU Conversion of existing BW Objects Report SAP_CDE_CONVERSION_DB6 Non-BLU -> BLU in online mode BLU -> BLU / Non-BLU in read-only mode Select an InfoCube or all InfoCubes "Get Dependent Tables" determines the tables belonging to the BW Object 14

15 Planned SAP BW Adoption for DB BLU Feature SAP NetWeaver BW 7.00 and higher Support expected to start with DB FP1 (End of 2013) DB BLU extensions are delivered with SAP BW support packages 15

16 How fast is it? Results from the DB nd Alpha Customer Tests Workload Speedup over DB Large Financial Services Company 46.8x Global ISV Mart Workload 37.4x Analytics Reporting Vendor 13.0x Common 8x-25x improvement Global Retailer 6.1x Large European Bank 5.6x Internal Benchmark Test 3.0x

17 DB2 = ONE 4 ALL Average diaglog response time 0,2-0,8 sec Average diaglog response time 0,4 2 sec DB2 LUW DB2 LUW DB2 LUW SAP Business-Suite, Industry Solutions OLTP workload SAP BW Big Data OLAP workload NLS for BW Near-line Storage Transactional Analytical Near-line Storage 17

18 DB2 - Tailored Performance for SAP Customers compared with non-virtualised and non-consolidated solution Customer runs DB2 on POWER/AIX systems, 48 production - 26 HA (LPM*) + 26 DR (PowerHA) - 2 data centers 4 POWER servers * LPM - AIX live partition mobility Implementation w/o virt. & consol systems, 48 production - 26 HA + 26 DR clusters - 2 BIGGER or more data centers - 48 servers for production - 52 servers for HA+DR clusters - up to 48 servers for test/qa - up to 48 servers for dev - up to 36 servers for rest servers 18

19 Compression and Storage Savings Often compression and storage savings are wrong determined database size consists of ALL data stored on storage (e.g not only tables) Comparing in-memory databases and on-disk databases should be done on the right level On-disk database RAM On-disk database storage In-memory DB RAM In-memory database storage 19

20 Cost Comparison for DB2 on Power vs. SAP HANA on Intel EXAMPLE: 10TB raw active user data DB BLU recommendation for 10TB of data is 500GB - 1TB of memory SAP recommendation for 10TB of data is 4TB - 5TB of memory DB BLU storage requirements for 10TB of SAP data is 1.4TB storage SAP storage requirements are = 4 * memory required = 16TB 20TB DB BLU CPU requirements for 10TB is 32 cores of Power7+ SAP HANA CPU requirements for same database is 320 cores of Intel Costs DB on 32core 770+ server (1TB DRAM & 2TB SSD storage) Software costs = DB2 AESE = $94K/TB = $188,000 (2TB of compressed data) Hardware costs = $878,884 Total = $1,066,884 (including 1 st year support) SAP HANA on 9 40-core IBM x3590 servers (512GB DRAM & 2.5TB storage each) Software costs = SAP HANA Enterprise Edition for 2TB compressed data = $6,106,000 Hardware costs = $$1,450,000 Total = $7,556,000 + $1,343,320 (1 st year S&S) = $8,899,320 SAP HANA is 834% more expensive than DB BLU on Power 2013 IBM Corporation

21 Was unterscheidet DB2-BLU von SAP-HANA? DB2- BLU Wettbewerbsvorteile durch neue und schnellere Prozesse SAP- HANA Wettbewerbsvorteile durch neue und schnellere Prozesse Standard- Hardware spezielle Appliance- Hardware Investitionssicherheit durch SAP-IBM- Kooperation volle Flexibiltät bei der Plattform Auswahl (inkl. IBM-Power-Plattform) Investitionssicherheit durch SAP- Komplettlösung reduzierte Plattform- Flexibiltät (nur freigegebene x86-systeme) Standard DB2-Betriebsaufwendungen spezielle Betriebsaufwendungen Lizenzkosten in DB2 AESE inkl. extra SAP- Lizenzzahlungen Storage- / Server- Kosten sinken Storage- / Server- Kosten steigen

22 First Customer Quotes on DB Significantly Less Storage, Better Performance 10x. That's how much smaller our tables are with BLU Acceleration. Moreover, I don't have to create indexes or aggregates, or partition the data, among other things. When I take that into account in our mixed table-type environment, that number becomes 10-25x. -Andrew Juarez, Lead SAP Basis and DBA When I converted one of our schemas into DB with BLU Acceleration tables, the analytical query set ran 4-15x faster. -Andrew Juarez, Lead SAP Basis and DBA What was really impressive is the fact that we could get significantly better performance with DB210.5 using BLU Acceleration without having to create indexes or aggregates on any of the tables. That is going to save us a lot of time when designing and tuning our workloads. - Kent Collins, Database Solutions Architect, BNSF Railway When we compared the performance of column-organized tables in DB2 to our traditional roworganized tables, we found that, on average, our analytic queries were running 74x faster when using BLU Acceleration. - Kent Collins, Database Solutions Architect, BNSF Railway

23 DB2 with BLU Acceleration Super analytics Super easy THANK YOU