MapR: Converged Data Pla3orm and Quick Start Solu;ons Robin Fong Regional Director South East Asia
Who is MapR? MapR is the creator of the top ranked Hadoop NoSQL SQL-on-Hadoop Real Database time streaming We provide the world s only converged data platform that can natively manage and protect all enterprise data within a single, global-scale system 2
MapR Fundamentals High-growth Premium Investors 700+ Customers > 100% Billings Growth < 1% Churn ~140% Net Expansion ~90% Software Subscriptions ~90% SW Billings Gr. Margin American Express United Healthcare 3
MapR is Helping to Transform Businesses $40M Revenue Driven From 1 of 15 use cases $10M+ Cost Savings Claim payment integrity 10%+ Increased Conversion Shopping on HP.com Fortune 50 Retailer $1B Additional Revenue Over 50 Applications $4B Yearly Savings Largest Biometric DB $100M Driven by Targeting My Offers 4
Architecting for Customer Production Success 2016 2004 2015 MapR 5.1 Converged Data Platform MapR 5.0: Extend real-time Hadoop to big data apps (Global Events Steaming) 2013 MapR-DB Real-time, in-hadoop DB 2011 MapR becomes Hadoop technology leader Built for the enterprise 2009 MapR in stealth Built for today s use cases 2004 2006 Hadoop developed at Yahoo! Google publishes details of GFS Built for as-it-happens, agile businesses 5
Leading Big Data Technologies on One Platform Hadoop Spark Streaming SQL-on-Hadoop NoSQL MapR not only provides a utility-grade platform for Apache Spark but converges it with MapR Streams and MapR-DB to power real-time global data applications. [MapR] has clearly thrown down the gauntlet to its competitors..it [MapR Streams] puts real time messaging right in the database machines can communicate in real time, globally, in a way that s resilient and secure. Schema Flexibility 25% Data Engine Interoperability 20% Pricing Model 20% Enterprise Manageability 15% Workload Role Optimization 10% Query Engine Maturity 10% 3.9 MapR SQL-on- Hadoop platforms Score Disruption Vectors 6
MapR: Real-Time and Reliable with Lowest TCO Online TCO Calculator for Hadoop: mapr.com/tco MapR Provides 30-50% lower TCO 7
Not All Big Data Platforms are the Same 8
Only MapR provides a converged data platform Sources/Apps Bulk Processing Stream Processing Utility-Grade Platform Services Data Enterprise Storage Database Event Streaming MapR-FS MapR-DB MapR Streams Global Namespace High Availability Data Protection Self-healing Unified Security Real-time Multi-tenancy Only full-stack big data platform. 9
Big Data Requires a Rock-Solid Architecture FOUNDATION 10
Apache Hadoop NameNode High Availability HDFS HA HDFS Federation A B C D E F A B C A D BE F C D A B E C F D E F A B C D E F NameNode Primary NameNode NameNode Standby NameNode NameNode NameNode NameNode NameNode Only Multiple Single one active point single of NameNode points failure of failure w/o HA Limited to 50-200 million files Needs 20 NameNodes for 1 Billion files DataNode DataNode DataNode DataNode DataNode DataNode DataNode DataNode DataNode HDFS-based Distributions Performance bottleneck Metadata must fit in memory Double the block reports 11
No-NameNode Architecture A B C D E F NameNode No special config to enable HA DataNode DataNode DataNode Up to 1T files (> 5000x advantage) Automatic failover & re-replication DataNode DataNode DataNode Significantly less hardware & OpEx Metadata is persisted to disk DataNode DataNode DataNode Higher performance 12
Key Reasons for Selecting MapR Respondents who had prior experience with another Hadoop distribution* * Apache Hadoop, Cloudera or Hortonworks 13
MapR Quick Start Solutions Faster deployments for most critical and valuable Hadoop use cases 1 2 3 Receive best practices for business team and IT organizations to get started Achieve faster time-to-value with pre-built solution templates Leverage world-class data engineers from MapR (and local partner) with proven results at most mature Hadoop customers 14
Quick Start Solutions Enabling customers see value from big data quickly Data Warehouse Optimization & Analytics Time Series Analytics Real-Time Security Log Analytics Data Data Engineering Math Math Data Science Business Value Genome Sequencing Recommendatio n Engine Self-Service Data Exploration 15
Speeding Time-to-Value Data Warehouse Optimization and Analytics & Offload Real-Time Security Log Analytics Solution Template Recommendation Engine Deployment Architecture Time Series Analytics Genome Sequencing Knowledge Transfer Self-Service Data Exploration 16
What s in the Quick Start Solution 6 nodes of MapR software 4-5 weeks of PS engagement 3 Hadoop Professional Certifications via ODT 17
Data Warehouse Optimization & Analytics Template 18
Recommendation Engine Template MapR Data Platform 19
Financial Services: Recommendation Engine & Real-time Targeting Targeting credit card customers with personalized real-time offers GLOBAL FINANCIAL SERVICES CORPORATION OBJECTIVES Increase revenue and customer loyalty through real-time personalized offers CHALLENGES Developers and analysts are unable to access all customer data Many different CRM tools and siloed targeting engines Required better reliability, performance, and ability to stream real-time data Want to increase speed and true personalization of recommendations SOLUTION MapR Enterprise DB Edition centralizes analytics and operational apps on one platform Integrates all customer online and offline data into one repository in realtime: card member spend graph, merchant data, location, and feedback Uses Mahout machine learning to provide real-time personalized offers Business Impact Increases revenue and improves customer experience through real-time targeting A more flexible, scalable platform that s a fraction of the cost of traditional technologies Ensures reliability with MapR high availability and disaster recovery features 20
Continuous Analytics at American Express Improve service to customers Facilitate commerce Make products more relevant Manage risk 21
American Express Facilitating Commerce with Amex Offers 22
American Express Managing Risk/Fraud Fraud protection on $1 trillion Decisions made in less than 2 milliseconds 23
Operations + Analytics = Real-time, Personalized Services Real-time Operational Applications Online transactions Fraud detection Personalized offers Fraud model Recommendations table MapR Converged Data Platform Fraud investigator Fraud investigation tool Clickstream analysis Interactive marketer Analytics 24
The Rise of IoT and Data in Motion By 2020, 21% of all high value data will come from IoT - IDC 1 Billion 1990s: Fixed Internet 6 Billion 2000s: Mobile Internet 50 Billion 2020: Internet of People and Things Connected Devices Worldwide 25
Stream Processing Solution Template Real-time Data Sources Smart Devices Producer Workflow Management Consumer Workflow Management Dashboard s Log Data Sensors Social Media Ingestion Service or Elastic Data Persistence Search Engine Analytics Applications Clickstream Converged Data Platform Search 26
Stream Processing Use Cases Cloud Provider: Real-time Monitoring Retail: Customer Location Optimization Telecom: Real-time Antenna Tuning Finance: Real-time Transaction Processing Real-time detection and alerting on service failures, security. Up-to-date customer usage and billing data, and overage alerts. Improved customer satisfaction by responding to traffic spikes in real time. Tighter security by providing real-time alerts of anomalous user locations or patterns. Improved customer satisfaction, reduced churn by responding to hot spots in real time. Effective, granular capacity planning. Improved user satisfaction with real-time mobile notifications of purchases. More fraud detected in real-time. More productive staff with data exploration. 27
Thank You Engage with us! @mapr maprtech mapr-technologies MapR rfong@mapr.com maprtech 28