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Big Data Performance Delivered : Oracle NoSQL DataBase on Cisco UCS

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  •  Q4FY12, Data Center revenue was up 90% y/y and up 42% q/q Q4FY12UCS bookings grew 58% Y/YQ4FY12 Cisco UCS achieved an annualized revenue run rate of over $1.6BAs of August 2012, we have over 15,800 UCS customers More than half of Fortune 500 companies have invested in Cisco UCSTotal number of repeat customers grew from 400 last year to 4,861 this year 347 customers have purchased over $1M and 813 customers have purchased over $500K in UCS product Total UCS Specialized Partners (ATP + UCT + DCA – any overlaps):  1200       (this is double the number vis-à-vis FY11 exit)Total Active Partners Selling UCS Products during FY12:                      2600• UCS revenue grew 57% Y/Y for FQ3-2012 • Cisco UCS achieved an annualized revenue run rate of over $1B.• As of May 2012, we have over 13,000 UCS customers • More than half of Fortune 500 companies have invested in Cisco UCS• Total number of repeat customers grew from 400 last year to 4,084 this year • 290 customers have purchased over $1M and 670 customers have purchased over $500K in UCS product  Over 2300 partners actively selling UCS over the past 12 months worldwide.Over 1000 UCS specialized partners in the channel worldwide. They hold at least one of our UCS specializations (ATP, DCA, UCT).
  • Our approach of integrating besf of breed storage, virtualization, applications, etc for customer focused solutions would not be feasible without the support and trust of our ecosystem of strategic technology partners. We are aligned with our partners both from a technology integration perspective and from a joint GTM perspective.
  • Notes:The results below are an extension of the Proven Track Record of Performance for Cisco UCS:• Cisco has consistently set world records on SPECjAppServer®2004, SPECjbb®2005, and SPECjEnterprise®2010 benchmarks, proving the breadth of enterprise middleware performance that Cisco Unified Computing System can deliver All three benchmarks are powered by the latest Intel Xeon E7 family of processorsSPECjEnterprise2010:What means to Cisco: Another in a series of Oracle based benchmarks that demonstrates the superiority of Cisco UCS over our competition. Specifically:World-record in any x86 based serversWorld-record in any 2-node SPECjEnterprise2010 configurationsHighest per-node SPECjEnterprise2010 performance What this means to Oracle: Demonstrates the performance superiority of Oracle Weblogic over its primary competitor IBM WebSphere.What this means to Customers: Customers should seriously consider Cisco UCS to run their enterprise applications particularly those like Oracle that run on Oracle Weblogic and Oracle Database Some additional ways to phase this: Now customers can run their enterprise applications on x86 based Cisco UCS servers with confidence while leaving behind the vendor lock-in associated with costly RISC processor–based servers.  The benchmark results demonstrate how Cisco delivers an end-to-end solution with the server and networking product breadth and depth necessary to outperform the rest of the x86 server industry.  This result demonstrates not just superior performance, but also how customers can power their enterprise applications with a high-performance system built on industry standards: the Cisco Unified Computing SystemSPECjbb2005:What means to Cisco: Another in a series of Oracle based benchmarks that demonstrates the superiority of Cisco UCS over our competition. Specifically:World-records in mainstream enterprise servers (in both 2-socket and 4-socket categories) By setting records with two servers simultaneously, Cisco shows how organizations can use their choice of 2 or 4-socket servers to power enterprise middleware with superior performance. While many server vendors have access to the same processors from Intel, only Cisco has incorporated the top-of-the-line Intel Xeon E7 family into a flexible, scalable, blade form factor. What this means to Oracle:Demonstrates the performance superiority of Oracle Java HotSpot Server over its primary competitor IBM Java 9 VMWhat this means for customers: Further proof that Cisco UCS is one of the very best platforms to drive their Oracle environments
  • Our solution in this space, called “ Common platform architecture”, is a rack level solution offer a balanced compute, capacity and IO bandwidth for demanding big data applications. Unique differentiation here is the ability to manage this from UCSM just like you have been managing your blade servers 
  • Framework for thinking about Big DataBig Data has 4 distinct stages of use: Acq, Org, Ana & Dec. For each stage you need to identify the technologies that you plan to use to storage, manage and manipulate the data. We’re going to focus on the Acquisition phase of using Big Data later on in this presentation. But at the end of day, Big Data is about using detailed knowledge/information about your business in order to make better business decisions.
  • Bottom line: NoSQL is about “data management scalability at cost” first and foremost. There are some technical features that are also important, but they come secondary. With enough effort (HW and SW) you can solve most of the technical problems with RDBMS systems. However, the whole reason that NoSQL was invented was to deal with the fact that it’s too expensive to manage Big Data using general purpose RDBMS systems. Regarding CAP: http://en.wikipedia.org/wiki/CAP_theoremThe CAP theorem, also known as Brewer's theorem, states that it is impossible for a distributed computer system to simultaneously provide all three of the following guarantees:Consistency (all nodes see the same data at the same time)Availability (a guarantee that every request receives a response about whether it was successful or failed)Partition tolerance (the system continues to operate despite arbitrary message loss)According to the theorem, a distributed system can satisfy any two of these guarantees at the same time, but not all three. RDBMS products focus on CA, where as NoSQL products focus on AP.
  • Bottom line: NoSQL is about “data management scalability at cost” first and foremost. There are some technical features that are also important, but they come secondary. With enough effort (HW and SW) you can solve most of the technical problems with RDBMS systems. However, the whole reason that NoSQL was invented was to deal with the fact that it’s too expensive to manage Big Data using general purpose RDBMS systems. Regarding CAP: http://en.wikipedia.org/wiki/CAP_theoremThe CAP theorem, also known as Brewer's theorem, states that it is impossible for a distributed computer system to simultaneously provide all three of the following guarantees:Consistency (all nodes see the same data at the same time)Availability (a guarantee that every request receives a response about whether it was successful or failed)Partition tolerance (the system continues to operate despite arbitrary message loss)According to the theorem, a distributed system can satisfy any two of these guarantees at the same time, but not all three. RDBMS products focus on CA, where as NoSQL products focus on AP.
  • Bottom line: NoSQL is about “data management scalability at cost” first and foremost. There are some technical features that are also important, but they come secondary. With enough effort (HW and SW) you can solve most of the technical problems with RDBMS systems. However, the whole reason that NoSQL was invented was to deal with the fact that it’s too expensive to manage Big Data using general purpose RDBMS systems. Regarding CAP: http://en.wikipedia.org/wiki/CAP_theoremThe CAP theorem, also known as Brewer's theorem, states that it is impossible for a distributed computer system to simultaneously provide all three of the following guarantees:Consistency (all nodes see the same data at the same time)Availability (a guarantee that every request receives a response about whether it was successful or failed)Partition tolerance (the system continues to operate despite arbitrary message loss)According to the theorem, a distributed system can satisfy any two of these guarantees at the same time, but not all three. RDBMS products focus on CA, where as NoSQL products focus on AP.
  • It’s “web applications” in the broadest sense. It’s applications that are capturing AND INTERACTING with massive amounts of data in real time, or applications that are providing web scale services for lots of small concurrent queries over simple data, or applications doing both. See the list of examples. Every industry has some of these. Highlight the ones that are relevant to the customer that you’re speaking with or add your own. The key differentiator is: a) high volume, b) high velocity, c) low intrinsic value. If it’s batch (not interactive) then it’s more likely to be an HDFS use case rather than NoSQL.
  • E-DBA built an online betting platform for live events – games, matches etc.  They get the scores in real-time from various feeds, show them to the Passoker customers who place bets in real-time.  This use-case really highlights the scalability and low latency aspect.
  • Oracle NoSQL Database - Simple Data ModelKey-value pair data structure, keys are composed of Major & Minor keysEasy-to-use Java API with simple Put, Delete and Get operationsCisco UCS – Radically simplified architectureSingle unified fabric requires one-third the network infrastructure to purchase, manage, and maintain.Intelligent infrastructure allows the entire system to be managed as a single logical entity within a higher-level framework Oracle NoSQL Database - ScalabilityAutomatic, hash-function based data partitioning and distributionIntelligent NoSQL Database driver is topology and latency aware, providing optimal data accessCisco UCS – On-demand scalabilityThe benefits of centralized computing delivered to the scale-out era Automated scaling is graceful, without a large incremental cost to deploy the first server in the next container, whether the container is a rack or a blade chassis.The system scales beyond the capacity of traditional blade chassis and encompasses multiple blade chassis and racks, managed as a single entityComplexity does not increase with size, helping to contain administration costs. Oracle NoSQL Database - Predictable behaviorACID transactions, configurable globally and per operationBounded latency via B-tree caching and efficient query dispatchingCisco UCS – HighperformanceDeterministic network latency - The Fabric Interconnect has deterministic latency and everything is connected through the Fabric InterconnectWorks very well in environments with bursty data due to high-bandwidth, low-latency cut-though switching architectureGet more performance out of Intel Xeon processors evidenced by World-record benchmarksOracle NoSQL Database - High Availability No single point of failureBuilt-in, configurable replicationResilient to single and multi-storage node failureDisaster recovery via data center replicationCisco UCS – Enterprise-class RASDesigned for no single-point-of-failureHigh reliability, availability, and serviceability helps reduce downtime and reduce TCO Intel Xeon processor E7 family offers advanced reliability features, including Machine Check Architecture Recovery, to automatically monitor, report, and recover from hardware errors to maintain data integrity and keep mission-critical services Oracle NoSQL Database - Easy AdministrationWeb console or command line interfaceSystem and node managementShows system topology, status, current load, trailing and average latency, events and alertsCisco UCS – Unified model-based management Self integrating and self aware: system automatically discovers and maintains an inventory of its components, integrating them into the system without any human intervention.XML API allows the system to be managed by higher-level, data center-wide management and orchestration systems for greater operational scale. You don’t have to take time keeping track of the system, the system keeps track of itself — saves time and money otherwise spent on integration and troubleshooting.
  • Transcript

    • 1. Big Data Performance Delivered:Oracle NoSQL Database on Cisco UCS Raghunath Nambiar, Distinguished Engineer, Cisco Ashok Joshi, Senior Director, Oracle© 2010 Cisco and/or its affiliates. All rights reserved. 1
    • 2. • Cisco Oracle Partnership and Cisco UCS Momentum • Cisco UCS Reference Configurations for Oracle NoSQL Database • Oracle NoSQL Database: Technology and Use Cases • Big Data Processing: An Analogy© 2010 Cisco and/or its affiliates. All rights reserved. 2
    • 3.  20 years of partnership Initially in networking, now extended to UCS  Foundational customers to each other  Joint engineering engagements Certifications Cisco Validated Design (CVD) Benchmarks  Growing Number of Joint Customers© 2010 Cisco and/or its affiliates. All rights reserved. 3
    • 4. © 2010 Cisco and/or its affiliates. All rights reserved. 4
    • 5. • In Q4FY12 Data Center Revenue increased 90% year over year and 42% quarter over quarter• In Q4FY12, UCS bookings increased 58%, year over year• As of Q4FY12 Cisco UCS achieved an annualized run rate of over 1.6 billion dollars• As of August 2012, there are over 15,800 unique UCS customers• More than half of all Fortune 500 customers have invested in UCS• 347 customers have booked over one million in UCS product and 813 have booked over $500,000• Over 2600 Channel Partners are actively selling UCS and over 1200 UCS specialized partners in the channel worldwide• 65 orld Record Performance Benchmarks to date© 2010 Cisco and/or its affiliates. All rights reserved. 5
    • 6. Worldwide UCS momentum is fueled by game-changing innovation; HP Cisco is quickly passing established players1X86 Server Blade Market Share, Q2CY121 IBM Cisco UCS #3 with 15.2% Dell x86 Blade servers are growing NEC over twice as fast as the overall Fujitsu x86 computing market2 Oracle Hitachi Ltd 0% 10% 20% 30% 40% 50% UCS After Only North America Three Years HP Maintained #2 in N. America Cisco UCS #2 with 21.9% (21.9%) and #2 in the US IBM (22.2%)1 Dell Maintained #3 worldwide in x86 Oracle Blades with 15.2%, just behind 0% 10% 20% 30% 40% 50% IBM’s 15.4%1 Source: 1 IDC Worldwide Quarterly Server Tracker, Q2 2012, August, 2012, Revenue Share 2 IDC Q1 CY12 Server Forecaster, Based on x86 Blade Revenue © 2010 Cisco and/or its affiliates. All rights reserved. 6
    • 7. © 2010 Cisco and/or its affiliates. All rights reserved. 7
    • 8. Smart Solutions Vblock Vertical Financial Information Solution Healthcare Manufacturing Retail Applications Services Operating Systems Focus Virtualization Compute Network Enterprise Databases Business Analytics Virtual Apps and Big Data Desktop VSPEX Applications FlexPod VXI Management RISC Operating Migration System and Hypervisor© 2010 Cisco and/or its affiliates. All rights reserved. 8
    • 9. A History of World Record Performance on Industry Standard Benchmarks SPECfp_rate_base2 SPECint_rate_base SPECfp_rate_base2 SPECint_rate_base SPECfp_rate_base2 SPECint_rate_base SPECfp_base2006 006 X86 2-socket 2006 X86 2-socket 006 X86 2-socket 2006 X86 2-socket 006 X86 4-socket 2006 X86 2-socket X86 2-socket C220 Best CPU B200 M1 B200 M1 B200 M2 B200 M2 C460 M1 C220 M3 M3 Performance SPECint_rate_base SPECfp_rate_base2 SPECint_rate_base SPECint_rate2006 SPECint_rate_base SPECfp_rate_base2 2006 X86 2-socket 006 2-socket 2006 2-socket X86 4-socket C460 2006 X86 4-socket 006 X86 2-socket B200 M2 C260 M2 C260 M2 M2 C460 M1 C220 M3 VMmark 1.x VMmark 1.x VMmark 1.x VMmark 1.x Best 2-socket B200 M1 2-socket B200 M1 2-socket B250 M2 Overall C460 M1 Virtualization VMmark 1.x VMmark 1.x Performance VMmark 1.x Blade Server B440 2 –socket Blade Overall C460 M1 M1 B230 M1 VMmark 2.1 VMmark 2.1 VMmark 2.1 2-socket Blade B200 Two–node 4-socket Best Cloud M2 4-socket C460 M2 C460 M2 Computing Performance VMmark 2.0 VMmark 2.1 Overall B200 M2 Overall C460 M2 Oracle E-Business Oracle E-Business Oracle E-Business Oracle E-Business TPC-C TPC-H 1000GB TPC-H 300GB Suite Ex-large Model Suite Medium Model Suite Xtra Large Suite Xtra Large Oracle DB 11g & Microsoft SQL VectorWiseBest Enterprise Payroll Batch B200 Order-to-Cash B200 Model Payroll Batch Model Payroll B200 OEL Server C250 M2 M2 M2 B230 M2 M3 C250 M2 C460 M2 Application Oracle E-Business Oracle E-Business Oracle E-Business SPECjEnteprise201 TPC-H 100GB Performance Suite Medium Model Suite Medium Model Suite Large Model SPECjEnterprise201 0 VectorWise Payroll Batch B200 Payroll Batch B200 Order-to-Cash B200 0 Overall B440 M1 2-node B440 M2 C250 M2 M2 M2 M3 SPECjAppServer20 SPECjbb2005 SPECjbb2005 SPECjAppServer20 SPECjbb2005 SPECjbb2005 04 X86 2-socket B200 X86 4-socket C460 04 X86 2-socket B230 X86 2-socket C220Best Enterprise 1-node 2-socket M2 M1 2-node B230 M1 M1 M3 Middleware C250 M2 SPECjbb2005 Performance X86 2-socket B230 SPECjbb2005 SPECjbb2005 SPECjbb2005 SPECjbb2005 2-socket C260 M2 2-socket B230 M2 2-socket B230 M2 4-socket B440 M2 M1 SPECompMbase20 SPECompLbase200 SPECompMbase200 SPECompMbase200 SPECompMbase200 LinPack LS-Dyna 01 1 1 1 1 2-socket B200 M2 4-socket C460 M1 Best HPC HPC Best HPC Performance 2-socket B200 M2 SPECompMbase20 2-socket B200 M2 SPECompLbase200 SPECompMbase20 SPECompLbase200 4-socket C460 M1 SPECompMbase200 4-socket C460 M1 SPECompMbase200 2-socket C240 M3 Performance 01 1 01 1 1 1 SPECompLbase2001 2-socket C220 M3 2-socket B200 M2 2-socket B200 M2 2-socket B230 M2 2-socket B230 M2 4-socket C460 M2 4-socket C460 M2 Cisco UCS Benchmarks that held world record performance records as of date of publication © 2010 Cisco and/or its affiliates. All rights reserved. 9
    • 10. World Record Benchmarks Performance Proof Points Oracle Application Standard Siebel 8.1.1.4 Benchmark 12.1.3 10,000 Users Payroll Batch – Extra Large kit Order to Cash Batch – Large kit B200 M3 JD Edwards 9.1 Oracle VM 2,000 Users Oracle Application Standard Benchmark 12.1.2 PeopleSoft 9.0 Payroll Batch – Extra Large kit North American Payroll Order to Cash Batch – Large kit 255,319 Payments/Hour B200 M3 TPC-C Two Socket YCSB Mix Wordkload 1,609,186.39 tpmC, $0.47/tpmC 1,244,550 Mix OPS/Sec C240 M3 23 World Record Oracle-based Benchmarks !© 2010 Cisco and/or its affiliates. All rights reserved. 10
    • 11. 7% faster, 11% less expensive than IBM using identical Intel 3% faster, 11% less processors and memory expensive than HP capacity 1,800,000 using identical Intel $1.40 processors and memory 1,609,186 tpmC 1,600,000 capacity 1,503,544 $1.20 $/tpmC TPC-C Price-Performance ($/tpmC) 1,400,000 New TPC-C Transactions-Per-Minute (tpmC) $1.00 1,200,000 1,024,380 1,053,100 1,000,000 $0.80 $0.65 800,000 $0.58 $0.53 $0.60 $0.47 600,000 $0.40 400,000 $0.20 200,000 0 $0.00 HP ProLiant DL380 G7 Cisco UCS C250 M2 IBM Flex System x240 Cisco UCS C240 M3 2 x Intel Xeon X5690 2 x Intel Xeon E5-2690 3.46 GHz 384GB Memory 2.90GHz 768GB Memory Westmere EP Romley EP * As of September27,2012. Visit www.tpc.org for up-to-date information© 2010 Cisco and/or its affiliates. All rights reserved. 11
    • 12. Using Yahoo! Cloud Serving Benchmark (YCSB)Cisco Big Data Common Platform (CPA) is a highly scalable architecturedesigned to meet variety of scale-out application demandsCPA Enhanced with Flash • Workload: YCSB Mixed workload (5% updates/95% reads) • Result: 1,244,550 OPS/Sec • 0.88 ms Read Latency • 4.47 ms Update Latency 2 x Intel Xeon E5-2690 Processors 128 GB Memory Cisco UCS VIC 1225 Twitter ~ 150API calls/sec© 2010 Cisco and/or its affiliates. All rights reserved. Source: http://blog.programmableweb.com/2011/05/25/who-belongs-to-the-api-billionaires-club/ 12
    • 13. © 2010 Cisco and/or its affiliates. All rights reserved. 13
    • 14. Big Data is Big Market & Big Business $50 Billion Market by 2017© 2010 Cisco and/or its affiliates. All rights reserved. 14
    • 15. • Major role in internet revolution. Global leader in networking• Complete Big Data platform portfolio with UCS• Areas of focus: Massive scale-out solutions including NoSQL and Hadoop• Exclusive partnership: Cisco UCS + Oracle NoSQL Database. Joint lab. Massive scale- testing• Differentiation: Seamless management integration and data integration capability with UCS Oracle infrastructure© 2010 Cisco and/or its affiliates. All rights reserved. 15
    • 16. Building Blocks Cisco Big Data Common Platform (CPA) is a highly scalable architecture designed to meet variety of scale-out application demands UCS Manager UCS 6200 Series Fabric Internments LAN, SAN, Management Nexus 2232Fabric Extenders UCS 240 M3 Servers© 2010 Cisco and/or its affiliates. All rights reserved. 16
    • 17. Reference Configurations 6200 Series FIs and 2232 Series FEX 16 x C240 M3 Servers 256 Processor Cores 160 Servers in a single 4 TB Memory (Up to 12 TB Supported) UCS Management domain 15K SAS : 113 TB 10K SAS: : 338 TB 10K Servers with 7.2K SATA : 384 TB UCS Central Flash : 20TB © 2010 Cisco and/or its affiliates. All rights reserved. 17
    • 18. Single magt interface Oracle Database Oracle NoSQL Global view of all components and Enterprise Database status inc failure power One click bios/fw upgrades Applications Cisco UCS C-Series Rack Mount Servers Cisco UCS B-Series Blade Servers Integrated Solutions: Internal IO bandwidth and Extendable to multi-data center FlexPod Unified management capacity implementations for disaster recovery Vblock Availability Seamless data integration and business continuity Backup Snapshot© 2010 Cisco and/or its affiliates. All rights reserved. 18
    • 19. Components Business Benefits UCS Fabric Interconnects provide Common Management Plane for Scale-out • Operational Simplification: Simplified &policy-based management to manage the UCS C-Series Rack servers with cluster Internal Storage provide the • Modular Solution: With Compute Nodes modular framework, infrastructure and expansion modules simplify deployment • Risk-reduction: Pre- validation, sizing and performance optimization reduces integration and deployment risk • Lower TCO: With reduced managed switch nodes in scale-out solutions Architectural Benefits• Scalability: Modular building block, scalable up to 2560 processor cores and 7.2 PB in single management domain• Performance: Best in class performance of compute and network for massively scale-out applications• Management & Monitoring: Unified management across cluster (up to 10000 nodes) © 2010 Cisco and/or its affiliates. All rights reserved. 19
    • 20. SmartPlay Solution Bundles Tested, validated and optimized for cost and rapid deployments © 2010 Cisco and/or its affiliates. All rights reserved. 20
    • 21. © 2010 Cisco and/or its affiliates. All rights reserved. 21
    • 22. © 2010 Cisco and/or its affiliates. All rights reserved. 22
    • 23. DECIDE ACQUIRE Make Better Decisions Using Big Data ANALYZE ORGANIZE© 2010 Cisco and/or its affiliates. All rights reserved. 23
    • 24. Endeca Information Oracle Business Application Discovery Intelligence EE NoSQL DB Driver Big Data Real Time Access Connectors Oracle Exalytics Big Data ORE, OEP, Endeca Acquisition Oracle Advanced Analytics OLH, ODC, Batch ODI, External Processing Tables HDFS, Hadoop, CDH Map Reduce Map Reduce Map Reduce ORCH - Stats Pig - Sessionize Hive - Activities Oracle Big Data Appliance Oracle Exadata© 2010 Cisco and/or its affiliates. All rights reserved. 24
    • 25. • Categories of big data solutions: Use new data in order to “enrich” value of existing databases and repositories Invent new applications with big data • Many technologies: NoSQL stores, distributed file systems, relational database systems… Simple key-value operations, map-reduce, SQL, Analytics, graph traversal, semantic analysis, spatial relationships, custom code… Endpoint facing” or end-user facing systems, storage, transformation, analytics and Business intelligence© 2010 Cisco and/or its affiliates. All rights reserved. 25
    • 26. Scalable, Highly Available, Key-Value Database Application Application Application Application Features NoSQL DB Driver NoSQL DB Driver • Simple Key-Value Data Model • Sharded, Horizontally Scalable • Highly Available • Elastic Configuration • Simple administration • Transparent load balancing • Commercial grade software and support Storage Nodes Storage Nodes Datacenter A Datacenter B© 2010 Cisco and/or its affiliates. All rights reserved. 26
    • 27. Scalable, Highly Available, Optimized • Scalability Dynamic data sharding (shared nothing) and distribution Optimized data access via intelligent driver • High availability One or more replicas Resilient to failures within a shard No single point of contention/control in entire system Disaster recovery through location of replicas • Transparent load balancing Reads from master or replicas Driver is network topology & latency aware© 2010 Cisco and/or its affiliates. All rights reserved. 27
    • 28. • High performance and predictable latency • Transactions and indexed access • Flexible schema – Diverse, changing data sets Key-value store; major key/minor key paradigm for modeling data • Horizontal scalability and Availability • Simplified management • Based on mature and proven technology Berkeley DB Java Edition High availability© 2010 Cisco and/or its affiliates. All rights reserved. 28
    • 29. • Cost TBs to PBs of simple/unstructured data Lower $ per operation (hardware and RDBMS license fees) • Scalability – Scale out, don’t scale up • Flexible schema – Diverse, changing data sets • Performance High rate of data capture High volume of simple queries Eliminate ORM overhead • Availability Low cost highly available, distributed data store© 2010 Cisco and/or its affiliates. All rights reserved. 29
    • 30. Oracle NoSQL Database Use Cases High-throughput data capture  Use Cases Customer profile management SIMPLE QUERIES Click-through data processing Sensor & statistics data capture DYNAMIC SCHEMA Social networks HIGH VOLUME Personalization Authentication & Content management REAL-TIME DATA Mobile application backend infrastructure ACCESS NoSQL Database is the “customer-facing” repository© 2010 Cisco and/or its affiliates. All rights reserved. 30
    • 31. Success Stories • - provides PaaS platform for deploying applications over the cloud Oracle NoSQL Database is exposed as a service through their cloud infrastructure • - Oracle Platinum Partner, built an online betting platform for their customer (Passoker) using Oracle NoSQL Database© 2010 Cisco and/or its affiliates. All rights reserved. 31
    • 32. Global Sports Betting application • Challenges Provide a platform for real-time sports data feeds Establish a technology to receive XML files and rapidly process them for relevance Reduce development time and simplify day-to-day administration Scale-out the platform as demand grows and players take up gaming in greater numbers • Benefits of Oracle NoSQL Database Reduced development and implementation time by 75% Simplified day-to-day administration Simplified rapid correlation between events and gaming Improved operational efficiency due to ongoing commercial support Eliminated daily maintenance related to single node point-of-failure Enabled more application development and integration, better testing, shorter time to market© 2010 Cisco and/or its affiliates. All rights reserved. 32
    • 33. Goal: Better, Faster Fraud Detection and Response Scenario •Credit card swipe at point of sale (PoS) •Look up customer profile (interactive) •Authorization systems determines approval •Approval sent to PoS and recorded Look Up Key Features •Fast response time, high throughput Authorization Approval Server Status •High availability and scalability •Huge transaction rates, simple data •Connectivity to Big Data Analytics and Discovery Record NoSQL DB Transaction© 2010 Cisco and/or its affiliates. All rights reserved. 33
    • 34. Goal: Better Patient Care at Lower Cost Scenario •Patient uses multiple devices at home •Medical data periodically sent to NoSQL DB •App monitors and alerts patient state •Alerts sent to medical or emergency personnel, recorded in profile Key Features Capture Patient •High performance and high availability Monitoring Data •High throughput event capture •Huge volumes of data •Simple data, flexible data model Alerting NoSQL System DB© 2010 Cisco and/or its affiliates. All rights reserved. 34
    • 35. Goal: Optimize Internet Advertising to Increase Revenues Scenario •User clicks on a web page •Cookie used to look up user profile •Appropriate ad placed on page Key Features Ad to be •Fast response times and high throughput Displayed •High availability and scalability Look Up User Profile •Simple data, flexible data model •Connectivity to Big Data Analytics and Discovery NoSQL Expert System DB© 2010 Cisco and/or its affiliates. All rights reserved. 35
    • 36. Architecture RDBMS Hadoop Cluster Ad Server Application NoSQL DB Driver Multi-Dimensional Reporting© 2010 Cisco and/or its affiliates. All rights reserved. 36
    • 37. • Problem Very low latency requirements – Publishers require < 75 ms response time from the ad serving platform Extreme data velocity – Multi-millions of requests per second Highly available – 24/7 sites Revenue maximization – Deliver the most relevant ad to maximize revenue • Solution – Where to use a NoSQL Database? Cookie store – NoSQL database used to store cookies and associated behavioral segments Track behavioral data – Beacons utilized during browsing to store timestamp, frequency, and behavioral segments by cookie Optimize ad delivery – Recency, frequency, and behavioral segments used to determine optimal ad to deliver to user© 2010 Cisco and/or its affiliates. All rights reserved. 37
    • 38. Oracle NoSQL Database Cisco UCS Radically simplified Simple data model architecture Easy to scale Modular scalability Predictive performance High performance High availability Fully redundant architecture Integration with UCS Oracle Database Infrastructure Enterprise-class service and support© 2010 Cisco and/or its affiliates. All rights reserved. 38
    • 39. Oracle on Cisco UCS www.cisco.com/go/oracle Oracle NoSQL Database http://www.oracle.com/us/products/database/nosql Cisco UCS Ecosystem for Oracle: Extend Support to Big Data and Oracle NoSQL Database http://www.cisco.com/en/US/solutions/collateral/ns340/ns517/ns224/ns944/le_34301_wp.PDF© 2010 Cisco and/or its affiliates. All rights reserved. 39
    • 40. © 2010 Cisco and/or its affiliates. All rights reserved. 40
    • 41. Thank you.