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Developing and Deploying Applications on the SAP HANA Platform

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Developing and Deploying Applications on the SAP HANA Platform

  1. 1. Developing and Deploying Analytic and Transactional Applications on the SAP HANA Platform Vitaliy @Sygyzmundovych Rudnytskiy, SAP SAPinsider HANA2015 Nice, June 2015 @SAPDevs #SAPHANA
  2. 2. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 1 Let’s start with… - … introduction :) - Vitaliy Rudnytskiy @Sygyzmundovych - SAP’s Developer Relations team - 12 years as a BI Technology Consultant - SAP Mentor 2010-2014 - Self-proclaimed King of Data Geeks  - Based in Wrocław
  3. 3. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 3 Agenda 10 Introduction() 20 SELECT "Key_Features" FROM SAP.HANA 30 Top Reasons -> Choose("SAP HANA") 40 SELECT Flexible_Choices FROM SAP.HANA 50 Wrap_Up()
  4. 4. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 5 Custom Applications Are Key to Modern IT Organizations seek to provide innovative technology and capabilities where it helps them compete and impact the business, while accepting more standardized packaged solutions in areas that do not necessarily require differentiating capabilities. IDC IT-developed applications have become the primary driver for growth and differentiation for enterprises. The building of these custom agile applications is becoming a hallmark of the new digital enterprise. Accenture Vision, 2014 Forrester Research: Don’t Just Maintain Business Applications, Raise Business Responsiveness, 2014 “ ” Packaged Applications 26% App Maintenance 49% Custom Applications 25% Business Software Spending*
  5. 5. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 8 SAP HANA: In-Memory Platform for All Applications JSONR Open ConnectivityMDXSQL Consumer-grade experience Application Services Database Services Integration Services Social Network Data Geospatial Data SAP HANA Platform Machine Data Text Data Structured Data For Cloud and On-Premise Open Interfaces In-Memory OLTP & OLAP All Data – one copy Embedded Libraries
  6. 6. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 10 Typical Application Architecture HANA as a Fast Data Engine HANA as an Integrated Platform Architectural Options to Use SAP HANA Platform Each Layer Takes Care of Partial Tasks of an Application Data Ingestion Business Logic Presentation logic Data Process Data Storage DB Client Application Server Application Server Application Server DB Application Server Client SAP HANA In-Memory Platform Client SAP HANA In-Memory Platform Development, crowd source … the project is great Development, crowd source … the project is great Development, crowd source … the project is great
  7. 7. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 11 Innovation Previously Unfeasible Mitsui Knowledge Industry – Cancer Cell Genomic Analysis Goal: transform comprehensive patient care to fight against cancer  Reduce the time to detect variant DNA  Support personalized patient therapeutics  DNA results 216x faster – in 20 minutes or less Streamline process of providing individualized cancer drug recommendation
  8. 8. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 13
  9. 9. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 14 Developer Licenses to Get Started UseDevelopLearn Trials/Sandboxes Free, time-limited development environments Developer Licenses Full development (free license, hosting costs may occure) Commercial Licenses For Customers and Partners Free Charge
  10. 10. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 15 SAP Developer Center: http://developers.sap.com • One-Stop Shop for SAP Developers • Structured by developer topics, including SAP HANA • Guided developer experience • Access to developer editions of SAP platforms and tools • Integrated with SAP.com and SCN  migrating towards 1DX
  11. 11. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 16 Helping you to get started with new SAP technologies SAP CodeJam is a 5 to 6 hours hands-on coding and networking event where attendees share their knowledge and collaboratively develop with SAP technologies, platforms and tools in a fun and casual environment. The events are developer community focused and supported by SAP, exploring technologies available through the SAP Developer Center. For more details on the CodeJam program or the multiple topics we offer, check out our page here: http://scn.sap.com/docs/DOC-37775
  12. 12. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 17 openSAP Cources: http://open.sap.com Keeping pace with the rapidly developing world of information technology is a need that SAP helps to fill with openSAP openSAP is developed and provided by SAP in cooperation with the Hasso Plattner Institute openSAP works according to the principle of "Massive Open Online Courses" (MOOC), but is not the replacement for formal SAP Education or SAP certification Some recent courses: Software Development on SAP HANA (Delta SPS 09) Build Your Own SAP Fiori App in the Cloud ABAP Development for SAP HANA
  13. 13. SELECT "Key_Features" FROM SAP.HANA Key SAP HANA Features for Application Development
  14. 14. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 19 SAP HANA Components for Application Development SQL JSON .NET J/ODBC OData HTML5 MDX XML/A R Application Services Database Services Integration Services Graph Data Geospatial Data SAP HANA Platform Machine Data Text Data Structured Data For Cloud and On-Premise
  15. 15. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 20 SAP HANA XS Engine Native SAP HANA Application Fully Leveraging In-Memory Computing SAP HANA Client Applications running on SAP HANA XS Engine that:  Provide powerful search services and built-in web server to access static content stored in SAP HANA repository  Optimize database connector to access in-memory data faster  Support attractive and dynamic HTML5 UI via OData services or by writing native application-specific code that runs in SAP HANA context Application development following a layered approach  UI rendering completely in the client (browser, mobile apps)  Server-side procedural logic in JavaScript  All artifacts stored in the SAP HANA repository Presentation logic Control flow logic Calculation logicData XS
  16. 16. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 21 Sample of some cool ideas from the community „A Simple Door Monitoring System with HANA XS and Raspberry Pi” by Ferry Gunawan http://scn.sap.com/community/developer-center/hana/blog/2014/07/09/build-a-door-sensor-with-raspberry-pi-and-hana
  17. 17. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 23 SAP HANA Smart Data Streaming • Capture, filter, analyze, and act on millions of events per second in real time • Capture high value data in HANA and direct other data into Hadoop • Stream live information to operational dashboards • Perform continuous queries using declarative (CCL) or model-driven approaches Incoming streams Stream (push) SAP HANA Streaming Service
  18. 18. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 24 Sample of some cool ideas from the community „HANA Smart Data Streaming in Action” by Eric Du http://scn.sap.com/community/developer-center/hana/blog/2015/03/17/hana-smart-data-streaming-in-action
  19. 19. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 25 SAP HANA Predictive Analysis 1 Predictive Analysis Libraries (PAL) Accelerate predictive analysis and scoring with native, in-database algorithms delivered out-of-the-box Graphical Modeling Pre-built commonly utilized business & predictive algorithms to facilitate a faster and easier development 2 R Integration Execute R scripts via high performing parallelized connection. Embed R scripts as part of overall query plan. Client Tools SAP Predictive Analysis, SAP InfiniteInsight, BI clients: SAP Lumira Partner Tools: SAS SAP Industry & LoB Applications Demand Signal Management, Fraud Management, Audience Discovery & Targeting, over 20 other Apps New Custom Built Applications In-Memory Processing Engine SQL Engine Text Engine Calculation Engine PAL1 R-Scripts2 Association Analysis Cluster Analysis Classification Analysis Time Series Analysis Outlier Detection Link Prediction Data Preparation … R-Engine
  20. 20. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 26 SAP HANA In-Memory Predictive Analytics Predictive Analysis Library (PAL) – Algorithms Supported Association Analysis • Apriori • Apriori Lite • FP-Growth • KORD – Top K Rule Discovery Classification Analysis • CART • C4.5 Decision Tree Analysis • CHAID Decision Tree Analysis • K Nearest Neighbour • Logistic Regression • Neural Network • Naïve Bayes • Support Vector Machine Regression • Multiple Linear Regression • Polynomial Regression • Exponential Regression • Bi-Variate Geometric Regression • Bi-Variate Logarithmic Regression Probability Distribution • Distribution Fit • Cumulative Distribution Function • Quantile Function Outlier Detection • Inter-Quartile Range Test (Tukey’s Test) • Variance Test • Anomaly Detection Link Prediction • Common Neighbors • Jaccard’s Coefficient • Adamic/Adar • Katzβ Data Preparation • Sampling - Random Distribution Sampling* • Binning • Scaling • Partitioning • Principal Component Analysis (PCA) Statistic Functions (Univariate) • Mean, Median, Variance, Standard Deviation • Kurtosis • Skewness Statistic Functions (Multi-variate) • Covariance Matrix • Pearson Correlations Matrix • Chi-squared Tests: - Test of Quality of Fit - Test of Independence • F-test (variance equal test) Other • Weighted Scores Table • Substitute Missing Values Cluster Analysis • ABC Classification • DBSCAN • K-Means • K-Medoid Clustering • K-Medians • Kohonen Self-Organized Maps • Agglomerate Hierarchical • Affinity Propagation Time Series Analysis • Single Exponential Smoothing • Double Exponential Smoothing • Triple Exponential Smoothing • Forecast Smoothing • ARIMA • Brown’s Exponential Smoothing • Croton Method • Forecast Accuracy Measure • Linear Regression with Damped Trend and Seasonal Adjust
  21. 21. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 27 Sample of some cool ideas from the community „Predicting My Next Twitter Follower with SAP HANA PAL” by Lucas Sparvieri http://scn.sap.com/community/developer-center/hana/blog/2013/09/02/predicting-my-next-twitter-follower-with-sap- hana-pal *PAL – Predictive Analysis Library
  22. 22. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 28 Spatial Processing with SAP HANA Gain Competitive Advantage by Uncovering New Insights with Native Spatial Processing Real-time Spatial Processing High-performance algorithms analyze massive amounts of spatial data in real time Mobility Visualization Analytics HTML5 GIS Applications Spatial Analytics Optimization Columnar storage architecture eliminates need to create spatial indexes, tessellation, or other optimization techniques Geo-content & services Maps, geo-content, and geospatial services open integration for seamless application development Spatial Data Types & Functions Store, process, manipulate, share, and retrieve spatial data directly in the database SAP HANA Spatial Processing Business Data + Spatial Data + Real-time Data Geo – Services - Geocoding - Base maps Geo – Content - Political Boundaries - POIs - Roads Columnar Spatial Processing - Clustering Calc Model/ Views - Joins - Views Spatial Functions - Area - Distance - Within Spatial Data Types - Points - Lines - Polygons Transaction Data Unstructured Data Location Data Machine Data
  23. 23. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 29 Examples of some cool ideas from the community „Experiences with SAP HANA Geo-Spatial Features” by Trinoy Hazarika http://scn.sap.com/community/developer-center/hana/blog/2014/02/25/experiences-with-sap-hana-geo-spatial- features-part-1
  24. 24. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 30 SAP HANA Text Analytic  Native full-text and fuzzy search  Exploit full-text search capabilities for exact, freestyle, linguistic, fuzzy, and synonym-based search and ranking  Info Access Toolkit  Rapid development of search-enabled applications through API and reusable UI building blocks  File Filtering  Unlock text from binary documents  Ability to extract and process unstructured text data from various file formats (txt, html, xml, pdf, doc, ppt, xls, rtf, msg)  Load binary, flat, and other documents directly into HANA for native text search and analysis  Native Text Analysis  Give structure to unstructured textual content  Expose linguistic markup for text mining uses  Classify entities (people, companies, things, etc.)  Identify domain facts (sentiments, topics, requests, etc.)  Supports up to 31 languages for linguistic mark-up and extraction dictionary and 11 languages for predefined core extractions SAP HANAInformation Access Services Suggestion Search Metadata Column Store Tables Metadata Search Model Search Engine Search Fuzzy Ranking Snippets Text Processor Linguistic Processing HANA Apps Applications and Analytics leveraging Text Search & Text Analysis capabilities Search UI configured with Info Access toolkit running natively on SAP HANA
  25. 25. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 31 Sample of some cool ideas from the community „Detecting World Cup GOAL using Twitter and SAP HANA” by Stevanic Artana http://scn.sap.com/community/developer-center/hana/blog/2014/07/03/goal-detection-using-twitter-and-sap-hana
  26. 26. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 32 SAP HANA Graph Engine • Manage property graphs within flexible, in-memory columnar store – faster queries and less storage • Combine graph with advanced analytics – text, predictive, geospatial – in a single transaction • Offer GEM language to traverse and manipulate graphs • No duplication of data to create graphs SAP HANA Graph Engine
  27. 27. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 33 Sample of some cool ideas from the community http://www.btw-2013.de/proceedings/The%20Graph%20Story%20of%20the%20SAP%20HANA%20Database.pdf
  28. 28. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 34 Application  Leverage remote database’s unique processing capabilities by pushing processing to remote database; monitors and collects query execution data to further optimize remote query processing  Compensate missing functionality in remote database with SAP HANA capabilities  Accelerate application development across various processing models and data forms with common modeling and development environment Merge Results SELECT from DB(x) SELECT from DB(y) SELECT from HIVE Application One SQL Script SAP HANA Virtual Tables Supported DBs as of SP6: HANA, Sybase ASE, IQ Hadoop/HIVE, Teradata Data-Type Mapping & Compensate Missing Functions in DB Modeling Environment Modeling Environment Modeling Environment Modeling and Development Environment Rapid Data Provisioning with Data Virtualization
  29. 29. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 35 Examples of some cool ideas from the community „HADOOP HDFS Explorer built with HANA XS and SAPUI5” by Aron MacDonald http://scn.sap.com/community/developer-center/hana/blog/2014/07/03/hadoop-hdfs-explorer-built-with-hana-xs-and- sapui5
  30. 30. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 36 SAP HANA with SAP Lumira Server Applications That Need Easy Ways to Implement Advanced Analytics  Native – SAP HANA XS application with Installation using SAP HANA Lifecycle Manager (LCM)  Robust with SAP HANA load balancing, failover, backup, recovery built-in  Secure – Identity and access management based on SAP HANA platform and users Lumira Datasets (real-time or static) Lumira Stories SAP Lumira SAP HANA 1. Build Lumira Data Sets/Views (Stored in SAP HANA) 2. Build Story (Stored in SAP HANA) 3. Visualize (uses Lumira Datasets/ Views and Stories stored inside SAP HANA) Faster results from real-time transactional data 1 2 3
  31. 31. Top Reasons -> Choose("SAP HANA") What Do Those Features Mean for You to Choose SAP HANA Platform?
  32. 32. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 39 Storage Storage CPU Memory CPU Memory Sub-Second Response, No Matter How Complex Process data and application logic in parallel (MPP), using all cores in a multi-core architecture, by effectively partitioning data Avoid unnecessary compensation (e.g., buffering, data duplication) during application execution by running application using the SAP HANA application services (built-in web server) Eliminate disk I/O by keeping all data in memory using column store and by significantly compressing data Access data faster using any column as index and by accessing only relevant columns via dictionary-encoded column store CPU Memory Bottleneck Data Hard Disk: 10,000,000ns*/SSD: 200,000ns* Disk Storage Log 60ns* L1 Cache L2 Cache L3 Cache 1.5ns* 4ns* 15ns* Core 1 Core N Any Column as Index Parallelized Query Query Compressed Data Log Copy into memory Code DB App Data (DB + App) SAP HANA Scan 3.2 billion integers/sec/core Aggregate 12.5 million integers/sec/core Ingest 1.5 million records/sec/node
  33. 33. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 40 Real-Time Applications, Zero Latency  Run both transactional and analytical applications on one single data model – Database tables designed to support simultaneous high volume/high speed transactional and analytical processing without compromising data consistency (ACID compliance)  Aggregate on-the-fly with no pre-materialization on key figures, including current transactions, using column store and parallel aggregation and the optimization for outer joins, distributed joins  Any delay of availability of transactional data for reporting or analytics has a major impact on business workflow; for example, period closing. SAP HANA can report (e.g., P&L) while we make adjustments, which is important for the consolidation.  The shorter response times enable users to increase the use of the system Traditional: OLTP and OLAP Separate 6 Hours 12:00:00 AM OLTP + OLAP in SAP HANA 10:00:00 AM 10:00:01 AM Immediate Current Data24-hour Old Data Aggregate ETL SAP HANA 6:00:00 AM
  34. 34. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 41 Embed sentiment fact extraction in same SQL Embed geospatial in same SQL Embed fuzzy text search in same SQL CREATE FULLTEXT INDEX i1 ON PSA_TRANSACTION( AMOUNT, TRAN_DATE, POST_DATE, DESCRIPTION, CATEGORY_TEXT ) FUZZY SEARCH INDEX ON SYNC; SELECT SCORE() AS SCR, * FROM "SYSTEM"."PSA_TRANSACTION" WHERE CONTAINS (*, 'Sarvice', fuzzy) ORDER BY SCR DESC; Click- stream Customer Data Connected Vehicles Smart Meter Point of Sale Mobile Structured Data Text Data RFIDMachine Data Support advanced text analytics Analyze text in all columns of table and text inside binary files with advanced text analytic capabilities such as automatically detecting 31 languages; fuzzy, linguistic, synonymous search using SQL. Structure unstructured data Use advanced text analytics, such as sentiment fact extraction, to structure unstructured data Analyze streaming data from integrated ESP in combination with data in HANA Process geospatial data Social Network SAP HANA Any Data SQL Geospatial Data Process Any Data, in Any Combination, Instantaneously with SQL
  35. 35. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 42 “ It is only a matter of scaling the hardware – there are no other variables or unknowns. SAP HANA: Re-Thinking Information Processing for Genomic and Medical Data, Prof. Dr. Hasso Plattner, 2013 ” Multi-core/ parallelization No disk PartitioningDistributed computing Scale Up Scale Out With the power of mathematics and distributed computing, SAP HANA can predictably complete any information processing tasks, however complex, within a given time-window • Need new IMC benchmark: introduces new capability, such as no aggregation or no indices, which needs new benchmark design • No pre-aggregated result: The test addresses the load-then- query ability without using any pre-caching results Extreme Linear Scalability Across Multi-Nodes Query processing time (in seconds) Query 1 Single customer and material for one month Query 2 Range of customers and material for one month Query 3 Year-over-Year trending report for Top 100 customers for 5 years SALES AND DISTRIBUTION REPORTS Linear Scalability to Meet Any Time Window
  36. 36. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 43 ODBC, JDBC SAP HANA  Easily migrate your applications (e.g., Java, PHP, .NET) using JDBC, ODBC, and OData/JSON  Build new web applications with any open source HTML5/JS libraries, Server Side JavaScript  Easy to bring data into HANA – Import data in CSV, Excel, or Binary formats. Load Geospatial files in shapefile, CSV, Binary, WKT, and WKB file formats. – Reuse current data sources with Data Virtualization – Replicate real-time data from multiple sources into SAP HANA for comprehensive data analysis  Open Cloud Partner Program allows you to select the best SAP HANA cloud deployment option from several partners App Services (Web Server) DB Services Browser/Mobile Web JS Lib Data Viz Lib Web App Server http(s),OData/JSON ODBO Third Party & Custom Application HTTP(S), OData, XML/A ODBC, JDBC, ADBC, ODBO MDX, SQL SQL Script Any HTML5/JS Library Stored Procedure Virtual Tables Import Real-time Replication CSV, Binary, shapefile, WKT, and WKB files Bring Your Own Code to an Open Platform
  37. 37. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 44 Browser/Mobile Web App Server DB Server SQL Stored Procedures http(s) Web JS Lib Data Viz Lib+ + HTML5/JS Libraries Browser/Mobile http(s), OData/JSON http(s) OLAPPredictiveText Mining BRM DB Server DB-oriented Logic Text Mining Predictive SQL Scripts R Integration Decision Tables SAP HANAApp LogicApp LogicApp Logic App LogicApp LogicApp Logic App LogicApp LogicApp Logic App LogicApp LogicApp Logic Aggregate + ++Flexible Table:  Push-down code: Replace application logic in multiple places with reusable DB logic written in SQL Script, consumed through OData  Efficient execution with built-in application services: Significantly improve application performance by running applications using SAP HANA application services (built-in web server) to avoid multiple layers of buffering and to reduce data transfers and processing logic  Optimized and open: Built-in SAPUI5 libraries with open integration to third-party libraries for both desktop and mobile user experience  Dynamic Schema: Dynamically add up to 64,000 columns with SQL Insert or Update statements without altering schema + App Services (Web Server) Procedural App Logic ODataJava Script Standard Table: Transformative Power, Simplified Programming
  38. 38. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 45 Apps SQL Script (Optimized Query Plan) Unstructured PALR-scriptsR Engine “The HANA platform at Cisco has been used to deliver near real-time insights to our execs, and the integration with R will allow us to combine the predictive algorithms in R with this near-real-time data from HANA. The net impact is that we will be able to take the capability, which takes weeks and months to put together, and deliver just in time as the business is changing. Piyush Bhargava, Distinguished Engineer IT, Cisco Systems (video) ” “See” the Future Accurately in Real-Time  Accelerate predictive analysis and scoring with in-database algorithms delivered out-of-the-box. Adapt the models frequently.  Execute R commands as part of overall query plan by transferring intermediate DB tables directly to R as vector-oriented data structures  Predictive analytics across multiple data types and sources. (e.g., Unstructured Text, Geospatial, Hadoop) C4.5 decision tree Weighted score tables Regression KNN classification K-means ABC classification Associate analysis: market basket Apps Virtual Tables OLAP Unstructured Predictive Logic R Logic Pre Process Pre Process Pre Process Geospatial
  39. 39. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 46 $ $ $ $ $ $ Web Application Server Enterprise Search Business Rule Management Predictive Analytics Planning Geospatial Data Warehouse Appliance ETL Event Processing Multiple Databases “Pointing to Glass' Law (sourced to Roger Sessions of ObjectWatch), which states that “for every 25 percent increase in functionality of a system, there is a 100 percent increase in the complexity of that system,” Gartner emphasizes the ability of an enterprise to get the most out of IT money spent. Gartner ” Text Analytics/Mining/Unstructured Data Development/Modeling Tools LifecycleMgmt/Admin/MonitoringTools  Simplify development, modeling, and administration environments with Eclipse-based tool  Reduce TCO: consolidating heterogeneous servers and data into SAP HANA servers to reduce the TCO for the system, backups, time for backups, and maintenance  Avoid hidden costs due to data quality, synchronization, and latency  Higher productivity: remove unnecessary tasks to get significantly higher productivity and help users focus on working on the material UnifiedDevelopment/Modeling/ Admin/MonitoringwithEclipse- basedtool SAP HANA Database Cache Data Warehouses De-Layer, De-Clutter. Consolidate!
  40. 40. SELECT Flexible_Choices FROM SAP.HANA ORDER BY 1 ASC
  41. 41. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 48 SAP HANA Appliance On-Premise SAP HANA One (Premium) Public Cloud SAP HANA Enterprise Cloud Managed Private Cloud Limited Scale Any Scale Elastic Scale SAP HANA SAP HANA  Choose hardware (Intel x86-based architecture) from hardware vendors HP, IBM, Fujitsu, Cisco, Dell, NEC, Hitachi, Huawei, and VCE as of July 2013  Scale as required  Real-time platform, infrastructure, and fully managed services from SAP or from our trusted partners  Bring your existing licenses to run all SAP HANA applications  Mission-critical, global, 24x7 operations  Start using SAP HANA right away  Managed by Amazon Web Services (AWS), Korea Telecom, Portugal Telekom, and VMware  60.5 GB instance size, allowing for 30 GB of data  HANA One: – 99¢ per hour. Pay as you use. Community Support.  HANA One Premium: – USD 75,000 per year including SAP Enterprise Support SAP HANA Choose and Change Deployment Options Any Time
  42. 42. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 49 SAP Cloud powered by SAP HANA Overview Product Portfolio Customer Systems SAP HANA SAP HANA Enterprise Cloud SAP HANA Cloud Platform Line-of-Business Apps (On-Premise) Private Cloud (Managed) Public Cloud Managed-Cloud-as-a-Service Platform-as-a-Service Software-as-a-Service People Customer SAP Business Suite SAP Business Warehouse SAP HANA Datamart … Build Extend Run applications Finance Supplier Custom infrastructure and maintenance New Apps Collaboration People SAP JamSoccer Health Consumer Startups Business Ariba Commerce Hybris Any DB Integration leads to new and innovative business processes
  43. 43. Wrap_Up()
  44. 44. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 52 SAP HANA Delivers Results for Business Today 1,700+ startups from 57 countries building applications on SAP HANA 509% ROI from building new application at University of Kentucky Forrester reports 37% cost savings for applications running a single system for OLAP and OLTP Simple financial application reduces data footprint by up to 37x 3,000 software & tech partners; 4,000 service partners 200+ Custom-built applications or PoCs running on SAP HANA platform
  45. 45. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 53 SAP Startups Focus http://startups.saphana.com
  46. 46. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 54 Endless Possibilities Build Real-Time Modern Applications to Transform Your Business Ad hoc Reporting Application Dynamically aggregate data at any granularity without pre- configuration Planning & Optimization Application MONTH S MT W T F S Run real-time planning or optimization to find the best solutions Hybrid Data Analytic Application change Course seminar learn evaluation knowledge discussion creativity scale developlearner critique Process or analyze multiple types of data, such as geospatial, text, or graph data Internet-of-Things Application Network-embedded devices or sensors to connect and change the world Predictive Application Predict the future based on deep analysis of history data Application Services Database Services Integration Services SAP HANA Platform
  47. 47. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 55 SAP HANA In-Memory Platform Ideal Platform for Next-Generation “Smart” Applications  HTTP(S), OData, XML/A  ODBC, JDBC, ODBO  SQL, MDX Easier Consumption: Easier Development:  JavaScript, HTML5  Connect any programming language  App/web services  Decision table Easier Processing:  NLP, Predictive, R-Integration  Spatial processing, ad hoc OLAP views  Data virtualization Easier Ingestion:  Replication, streaming, ETL/ELT  Integration, data cleansing Personalized recommendation with machine learning, predictive, and rules Natural language processing Process any variety/ volume (e.g., unstructured) Respond within predictable time windows Key capabilities required for next-generation “Smart” applications: SAP HANA is a high-speed processing platform to enable:
  48. 48. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 56 Learn  SAP HANA Academy  SAP Open Courses  SAP Developer Network  SAP App Development Partner Center Try  SAP HANA Developer Edition  SAP HANA Cloud Platform  SAP Idea Incubator  SAP HANA One Experience  SAP HANA Customer Stories  SAP HANA Use Case Map  SAP Customer Journey iPad App  SAP HANA Use Case Repository Where to Find More Information
  49. 49. 57© 2015 SAP SE or an SAP affiliate company. All rights reserved. Open Leverage existing investments with an open platform 6 Speed Sub-second response, no matter how complex 1 Real-Time Real-time applications, zero latency 2 Any Data Process any data, in any combination, instantaneously with SQL 3 Any Source Rapid data provisioning with data virtualization 4 Consolidation De-layer, de-clutter. Consolidate! 9 Simplicity Transformative power, simplified programming 7 Prediction “See” the future accurately in real time 8 Predictable Completion Linear scalability to meet any time window 5 Choice Choose and change deployment options any time 10
  50. 50. © 2015 SAP SE or an SAP affiliate company. All rights reserved. Thank("you")! Vitaliy Rudnytskiy SAP Developer Center http://developers.sap.com http://twitter.com/sygyzmundovych http://scn.sap.com/people/vitaliy.rudnytskiy http://about.me/witalij
  51. 51. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 59 © 2015 SAP SE or an SAP affiliate company. All rights reserved. No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission of SAP SE or an SAP affiliate company. SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. Please see http://global12.sap.com/corporate-en/legal/copyright/index.epx for additional trademark information and notices. Some software products marketed by SAP SE and its distributors contain proprietary software components of other software vendors. National product specifications may vary. These materials are provided by SAP SE or an SAP affiliate company for informational purposes only, without representation or warranty of any kind, and SAP SE or its affiliated companies shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP SE or SAP affiliate company products and services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty. In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document or any related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation, and SAP SE’s or its affiliated companies’ strategy and possible future developments, products, and/or platform directions and functionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for any reason without notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, or functionality. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions.

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