Impact of in-memory technology and SAP HANA (2012 Update)


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Presented at ASUG SAP BusinessObjects User Group conference in 2012

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Impact of in-memory technology and SAP HANA (2012 Update)

  1. 1. September 10-13, 2012 Orlando, FloridaImpact of In-Memory Technology andSAP HANA on Your Business, IT, and Career (updated for 2012)Vitaliy Rudnytskiy, Developer Experience (DevEx), SAPDave Carlisle, HP-IT, Hewlett-Packard
  2. 2. Learning Points  As SAP keeps executing on its in-memory vision, SAP In-memory technology is becoming the major piece in SAP solutions portfolio (SAP, BusinessObjects, Sybase)  It is not just a niche toy for few übergeek experts anymore, but is reshaping the way business and IT are going to use SAP solutions, and it is impacting the set of skills required  Look at the different layers of this technology and its extended landscape, and how they are mapped into the skills required by different roles in your business and IT teams “The noblest pleasure is the joy of understanding” - Leonardo da Vinci2
  3. 3. Broader view on In-memory from SAP  Applications for in-memory computing  Customers home-grown solutions or off-the-shelf products delivered by SAP or SAP partners  Products can be brand new, or existing, but re-worked to benefit from in-memory technology  SAP HANA as a platform  As an appliance or in the cloud  Bundled software products depending on the license  In-memory technology  Pretty wide term to describe everything that enables highly efficient storage and high performing processing of (sometimes substantial) data volumes3
  4. 4. Major principles of SAP in-memory technology  Keep all required data (aka “hot data”) in main memory  Compress data to minimize the footprint by utilizing column storage  Disk I/O is no longer an optimization target  No need for pre-aggregated stores and multiple DB indexes  Rarely accessed data (aka cold data) can be moved to cheap storage  Cache sensitive data layout and cache-aware algorithms  High locality (data that is needed together is stored together)  Late materialization (decompress in cache)  Software performance growth is in parallel processing, not clock speed  Move data-intensive operations to the data layer  Requires application logic in data layer (example: currency conversion) “By 2012, 70% of Global 1000 organizations will load detailed data into memory as the primary method to optimize BI application performance.” - Gartner4
  5. 5. Learn It! Open web course from Week 1 (03.09.12 - 10.09.12) Week 4 (24.09.12 - 01.10.12) The Future of Enterprise Computing: In-Memory Database Operators Part 3: Introduction Aggregate Functions New Requirements for Enterprise Computing Parallel Select Enterprise Application Characteristics Workload Management Changes in Hardware Parallel Join You A Blueprint of SanssouciDB Parallel Aggregation still can Week 2 (10.09.12 - 17.09.12) Week 5 (01.10.12 - 08.10.12) enroll! Foundations of Database Storage Techniques Advanced Database Storage Techniques: and In-Memory Database Operators Part 1: Differential Buffer Dictionary Encoding Insert-only Compression Merge Data Layout in Main Memory Logging Partitioning Recovery Delete On-the-fly Database Reorganization Insert Update Week 6 (08.10.12 - 15.10.12) Tuple Reconstruction Foundations for a New Enterprise Application Scan Performance Development Era: Implications Week 3 (17.09.12 - 24.09.12) Views In-Memory Database Operators Part 2: Handling Business Objects Select Bypass Solution Materialization Strategies Parallel Data Processing Week 7 (15.10.12 - 22.10.12) Indices Final Exam Join5
  6. 6. SAP In-Memory Technology Evolution Source: “SAP HANA Essentials”, Jeffrey Word6
  7. 7. SAP HANA Database Architecture7
  8. 8. Read It! Some Good Books “In-Memory Data Management: Technology and Applications”, Hasso Plattner, Alexander Zeier, 2nd ed. “SAP HANA Essentials”, Jeff Word Voucher-Code 17C55987 for free download8
  9. 9. Data Mart Use Cases with SAP HANA and BI  Data Marts are more narrow in scope comparing to the data warehouse: focused on selected subject areas, moderate volumes and typically one source system  Data Mart use cases with SAP HANA and SAP BusinessObjects  Operational Data Marts  Getting data from business application (most typical is SAP ERP, but not necessarily) in the near real-time fashion using replication technology  Lightly transformed source data  Additional transformations based on non-materialized views  Agile Data Marts  Getting highly transformed data from a broader range of the SAP and non-SAP source systems in the batch fashion using SAP DataServices9
  10. 10. Major Principles of SBOP Integration with SAP HANA  There is very limited integration available between SAP BusinessObjects XI 3.1 and SAP HANA 1.0  For optimal integration between SAP BusinessObjects 4.0 and SAP HANA 1.0 make sure both systems are on matching Service Pack and patch levels  See SAP Note 1577128 - Supported clients for SAP HANA 1.0 for details  SAP HANA database can be used only as a reporting database with SAP BusinessObjects BI Platform 4.0 SP2  As of 4.0 FP3 you can use SAP HANA database as well as a CMS and Auditing database10
  11. 11. Authentication in SAP HANA Database  Access to the SAP HANA database is secured by authentication  Direct logon to the database with user name and password  Kerberos (single sign-on)  The SAP BusinessObjects Business Intelligence platform only provides single sign-on (SSO) authentication from FP3 of the release 4.0 for SAP HANA database 1.0 SP3 through JDBC on MS Windows and Linux platforms  Once users are logged on to the BI platform from an SAP BusinessObjects application by using their Windows AD credentials, they can perform actions that require database access, such as refreshing Web Intelligence documents, without providing their database credentials11
  12. 12. Authorizations in SAP HANA Database  For data access SAP HANA database provides the authorization concept based on two privilege types  SQL privileges (access to database objects such as tables, SQL ownership concept)  Analytical privileges (filters on information models for reporting purposes, for read operations only)  Having analytical privileges built into the SAP HANA database allows unified data access management from different BI tools: Universe-based, SBO Analysis for MS Office, MDX-enabled  There is no automated user and roles provisioning in SAP HANA database from SAP BusinessObjects BI Platform at the moment12
  13. 13. Practice It! SAP HANA Developer Center  Two options  Try&Test (30-days)  Includes Visual Intelligence, SBO Analysis, Explorer  Free SAP HANA Development License +  Forums  Blogs  E-Learnings etc13
  14. 14. SAP HANA DevCenter: facts speak better than words14
  15. 15. Try It! SAP InnoJam  Multiple locations  Design Thinking  30 hours of coding  HANA DB  BusinessObjects  Mobile  etc15
  16. 16. Key Learnings 1. It’s time to learn about SAP in-memory technology – an unavoidable trend for all SAP customers – and start assessing its impact on your business and IT 2. Get the holistic picture – learn to distinguish three overlapping but different layers – technology, platforms, and applications – and chart the roadmap for each of them in your planning 3. Think early about how to do proper landscape planning satisfying all requirements to realize the ultimate promise of the HANA platform capable of simultaneous handling both OLTP and OLAP processing “A man paints with his brain and not with his hands” -Michelangelo16
  17. 17. To find even more  From Dave:   Video “HP Business Results with SAP HANA” (  From Vitaliy:   Twitter: @VitalBI, @Sygyzmundovych  Blog:  From SAP Communities:  BI SIGs at  Forum at SCN:  From SAP:  http://www.ExperienceSAPHANA.com17
  18. 18. Thank you for participating. Please provide feedback on thissession by completing a short survey via the event mobile application. SESSION CODE: 1214 Learn more year-round at