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Neo4j GraphTalks - Einführung in Graphdatenbanken
The document announces a Neo4j GraphTalks event in October 2016 in Berlin. It includes an agenda with presentations on ADAMA's use of Neo4j for data sharing and knowledge management, and their experiences implementing and demoing Neo4j. There will also be an open networking session with NeoTechnology and PRODYNA representatives.
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Neo4j GraphTalks - Einführung in Graphdatenbanken
- 1. Neo4j GraphTalks Herzlich Willkommen! ! ! ! ! Oktober2016! bruno.ungermann@neotechnology.com
- 2. Neo4j GraphTalks ! • 09:00-09:30 Frühstück und Networking • 09:30-10:00 Einführung in Graph-Datenbanken und Neo4j (Bruno Ungermann, Neo4j) • 10:00-10.30 ADAMA: From Data Sharing to Knowledge Management (Georgiana Francescotti, Digital & Knowledge Services, ADAMA AGRICULTURE B.V.) • 10.30-11.00 ADAMA: Erfahrungswerte aus der Implementierung und Demo (Darko Krizic, CTO PRODYNA AG) • Open End (PRODYNA: Christoph Körner, Moritz Schmidt, Michael Joszt, Buket Oezcan, Lena Hawelky NeoTechnology: Dirk Möller, Alexander Erdl)
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- 5. Domain Model LogisticsProcess
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- 7. Graph Model: Nodes& Relationships Container ! Load! USING ROUTE Depart 2014-04-15 Arrive 2014-04-28 FROM TO USING ROUTE Depart 2014-04-15 Arrive 2014-04-28 FUELING USING_CARRIER LOAD USING CARRIER Vessel! Physical ! Container! Container ! Load! Shipment! Carrier! Emission! Class A! Shipment! Carrier! Route! 10520km! Route! 823km! ! Fueling! Max Weight 80! Type of Gas B! ! Town:! Tokyo! Town:! Hong Kong! Town:! Hamburg! Container ! Load!Container ! Load!Container ! Load! Parcel ! Weight 15.5kg!
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- 9. A Naturally AdaptiveModel Flexibility
- 10. “We found Neo4jto be literally thousands of times faster than our prior MySQL solution, with queries that require 10-100 times less code. Today, Neo4j provides eBay with functionality that was previously impossible.” - Volker Pacher, Senior Developer “Minutes to milliseconds” performance Queries up to 1000x faster than other tested database types! Speed
- 11. Discrete Data Minimally connecteddata Neo4j is designed for data relationships Other NoSQL Relational DBMS Neo4j Graph DB Connected Data Focused on Data Relationships Development Benefits Easy model maintenance Easy query Deployment Benefits Ultra high performance Minimal resource usage Use the Right Database for the Right Job
- 12. 2000 2003 20072009 ! 2011! 2013! 2014! 2015!2012! GraphConnect, first conference for graph DBs First Global 2000 Customer Introduced first and only declarative query language for property graph Published O’Reilly book on Graph Databases First native graph DB in 24/7 production Invented property graph model Contributed first graph DB to open source Extended graph data model to labeled property graph 150+ customers 50K+ monthly downloads 500+ graph DB events worldwide Neo4j: The Graph Database Leader
- 13. Financial Services Communications Health & Life Sciences HR& Recruiting Media & Publishing Social Web Industry & Logistics Entertainment Consumer Retail Information Services Business Services Neo4j Leads the Graph Database Revolution
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- 15. “Forrester estimates thatover 25% of enterprises will be using graph databases by 2017” “Neo4j is the current market leader in graph databases.” “Graph analysis is possibly the single most effective competitive differentiator for organizations pursuing data-driven operations and decisions after the design of data capture.” IT Market Clock for Database Management Systems, 2014 https://www.gartner.com/doc/2852717/it-market-clock-database-management TechRadar™: Enterprise DBMS, Q1 2014 http://www.forrester.com/TechRadar+Enterprise+DBMS+Q1+2014/fulltext/-/E-RES106801 Graph Databases – and Their Potential to Transform How We Capture Interdependencies (Enterprise Management Associates) http://blogs.enterprisemanagement.com/dennisdrogseth/2013/11/06/graph-databasesand-potential-transform-capture-interdependencies/ Neo4j Leads the Graph Database Revolution
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- 17. NEO4j USE CASES RealTime Recommendations Meta Data Management Fraud Detection Identity & Access Management Graph Based Search Network & IT-Operations Logistik RD BM S CRM RD BM S Mails Ma ils yst Dokume nte Fil es ys em Media Library Fil es ys em CMS RD BM S Social RD BM S LogFiles RD BM S Ecommer ce RD BM S HASOPENED_ACCOUNT BRIDGES POWERS POWERS INCLUD E INCLUD E CREA TE IN SOUR CE IN IN TRUST S TRUST S AUTHENTICAT ES CAN_RE AD
- 18. ! Business Problem • Optimizewalmart.com user experience • Connect complex buyer and product data to gain super-fast insight into customer needs and product trends • RDBMS couldn’t handle complex queries Solution and Benefits • Replaced complex batch process real-time online recommendations • Built simple, real-time recommendation system with low-latency queries • Serve better and faster recommendations by combining historical and session data Background • Founded in 1962 and based in Arkansas • 11,000+ stores in 27 countries with walmart.com online store • 2M+ employees and $470 billion in annual revenues Walmart RETAIL Real-Time Recommendations!18!
- 19. ! Background • One ofthe world’s largest logistics carriers • Projected to outgrow capacity of old system • New parcel routing system Single source of truth for entire network B2C and B2B parcel tracking Real-time routing: up to 7M parcels per day Business Problem • Needed 365x24x7 availability • Peak loads of 3000+ parcels per second • Complex and diverse software stack • Need predictable performance, linear scalability • Daily changes to logistics network: route from any point to any point Solution and Benefits • Ideal domain fit: a logistics network is a graph • Extreme availability, performance via clustering • Greatly simplified routing queries vs. relational • Flexible data model reflect real-world data variance much better than relational • Whiteboard-friendly model easy to understand! Accenture LOGISTICS 19! Real-Time Routing Recommendations!
- 20. ! Background • Second largestcommunications company in France • Based in Paris, part of Vivendi Group, partnering with Vodafone Solution and Benefits • Flexible inventory management supports modeling, aggregation, troubleshooting • Single source of truth for entire network • New apps model network via near-1:1 mapping between graph and real world • Schema adapts to changing needs Network and IT Operations ! SFR COMMUNICATIONS Business Problem • Infrastructure maintenance took week to plan due to need to model network impacts • Needed what-if to model unplanned outages • Identify network weaknesses to uncover need for additional redundancy • Info lived on 30+ systems, with daily changes LINKED LINKED DEPENDS_ON Router Service Switch Switch Router Fiber Link Fiber Link Fiber Link Oceanfloor Cable 20!
- 21. ! Background • Oslo-based telcomprovider is #1 in Nordic countries and #10 in world • Online, mission-critical, self-serve system lets users manage subscriptions and plans • availability and responsiveness is critical to customer satisfaction Business Problem • Logins took minutes to retrieve relational access rights • Massive joins across millions of plans, customers, admins, groups • Nightly batch production required 9 hours and produced stale data Solution and Benefits • Shifted authentication from Sybase to Neo4j • Moved resource graph to Neo4j • Replaced batch process with real-time login response measured in milliseconds that delivers real- time data, vw yday’s snapshot • Mitigated customer retention risks Identity and Access Management ! Telenor COMMUNICATIONS SUBSCRIBED_BY! CONTROLLED_B Y! PART_OF!USER_ACCESS! Account! Customer! Customer!User! Subscription! 21!
- 22. ! Background • Top investmentbank with $1+ trillion in assets • Using a relational database and Gemfire to manage employee permissions to research document and application-service resources • Permissions for new investment managers and traders provisioned manually Business Problem • Lost an average of 5 days per new hire while they waited to be granted access to hundreds of resources, each with its own permissions • Replace an unsuccessful onboarding process implemented by a competitor • Regulations left no room for error Solution and Benefits • Store models, groups and entitlements in Neo4j • Exceeded performance requirements • Major productivity advantage due to domain fit • Graph visualization ease permissioning process • Fewer compromises than with relational • Expanded Neo4j solution to online brokerage London Investment Bank FINANCIAL SERVICES Identity and Access Management!22!
- 23. ! Background • Global financialservices firm with trillions of dollars in assets • Varying compliance and governance considerations • Incredibly complex transaction systems, with ever- growing opportunities for fraud Business Problem • Needed to spot and prevent fraud detection in real time, especially in payments that fall within “normal” behavior metrics • Needed more accurate and faster credit risk analysis for payment transactions • Needed to dramatically reduce chargebacks Solution and Benefits • Lowered TCO by simplifying credit risk analysis and fraud detection processes • Identify entities and connections uniquely • Saved billions by reducing chargebacks and fraud • Enabled building real-time apps with non-uniform data and no sparse tables or schema changes London and New York Financial FINANCIAL SERVICES Fraud Detection! s! 23!
- 24. ! Background • Panama basedlawyers Mossack & Fonseca do business in hosting “letterbox companies” • Suspected to support tax saving and organized crime • Altogether: 2.6 TB, 11 milo files, 214.000 letter box companies Business Problem • Goal to unravel chains Bank-Person–Client– Address–Intermediaries – M&F • Earlier cases: spreadsheet based analysis (back- and-forth) & pencil to extract such connections • This case: sheer amount of data & arbitrarily chain length condemn such approaches to fail Solution and Benefits • 400 journalists, investigate/update/share, 2 people with IT background • Identify connections quickly and easily • Fast Results wouldn‘t be possible without GraphDB Panama Papers Fraud Detection Fraud Detection!24!
- 26. MDM Status Quo– viele kleine Königreiche Dr. Andreas Weber | semantic data management | 11.11.2016 ! QS / LIMS ERP Logistik Warehouse- management Produkt-management Technisches PDM/PLM Dokumenten- management Excel Excel Power-point Power-point Excel Excel
- 27. ! Adidas Meta DataManagement 27! Shared Meta Data Service! Background • Global leader in sporting goods industry services firm footware, apparel, hardware, 14.5 bln sales, 53,000 people • Multitude of products, markets, media, assets and audiences Business Problem • Beset by a wide array of information silos including data about products, markets, social media, master data, digital assets, brand content and more • Provide the most compelling and relevant content to consumers • Offering enhanced recommendations to drive revenue Solution and Benefits • Save time and cost through stadardized access to content sharing-system with internal teams, partners, IT units, fast, reliable, searchable avoiding reduandancy • Inprove customer experience and increase revenue by providing relevant content and recommentations
- 28. ! Background • Mid-size Germaninsurer founded in 1858 • Project executed by Delvin, a subsidiary of die Bayerische Versicherung and an IT insurance specialist Business Problem • Field sales needed easy, dynamic, 24/7 access to policies and customer data • Existing DB2 system unable to meet performance and scaling demands Solution and Benefits • Enabled flexible searching of policies and associated personal data • Raised the bar on industry practices • Delivered high performance and scalability • Ported existing metadata easily Die Bayerische INSURANCE Master Data Management!28!
- 29. ! Background • Leading EuropeanAirline • 100+ mln passengers • 2+ mln tons freight per year • 700+ aircrafts Business Problem • Need for flexible high performant Inflight Asset Management, onboard entertainment, byod • Complex data set: CMDB, CMS, Aircraft data feed, media library • Maintain individual configuration for each Aircraft • Complex data model, aircrafts, hardware, vitual containers, licenses, business rules, versions, content ... Solution and Benefits • Neo4j powers integrated platform that provides fast access to all aspects needed to maintain complex system • Fast implementation • Higly flexible data model enable constant evolution Lufthansa Digital Asset Mangagement 29! Graph Based Search, Metadata Management!
- 30. ! Background • Toy Manufacturer,founded 80+ years ago, plastic figurines sold in 50+ countries • 100 Mio, 250 employees • Production Process in different countries like China • Polymer Processing, Children‘s toys, high responsibility Business Problem • Product related data stored in many different data stores including SAP, Navision, Laboratory Systems, Document Systems, Powerpoint, Excel.. • Hard to find correct answers for authorities, , internally, parents Solution and Benefits • Neo4j powers integrated platform that provides visibility across whole supply chain • Domain Experts create and evolve data model • Correct answers within seconds Schleich Product Information Management 30! Master Data Management!
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