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New opportunities for connected data : Neo4j the graph database

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  • Social networksRecommendations enginesBusiness intelligenceGeospatial applicationsMDMNetwork and systems managementProduct catalogueWeb analyticsIndexing your slow RDBMS
  • Social networksRecommendations enginesBusiness intelligenceGeospatial applicationsMDMNetwork and systems managementProduct catalogueWeb analyticsIndexing your slow RDBMS
  • Social networksRecommendations enginesBusiness intelligenceGeospatial applicationsMDMNetwork and systems managementProduct catalogueWeb analyticsIndexing your slow RDBMS
  • Social networksRecommendations enginesBusiness intelligenceGeospatial applicationsMDMNetwork and systems managementProduct catalogueWeb analyticsIndexing your slow RDBMS
  • Social networksRecommendations enginesBusiness intelligenceGeospatial applicationsMDMNetwork and systems managementProduct catalogueWeb analyticsIndexing your slow RDBMS
  • Social networksRecommendations enginesBusiness intelligenceGeospatial applicationsMDMNetwork and systems managementProduct catalogueWeb analyticsIndexing your slow RDBMS
  • Social networksRecommendations enginesBusiness intelligenceGeospatial applicationsMDMNetwork and systems managementProduct catalogueWeb analyticsIndexing your slow RDBMS
  • Social networksRecommendations enginesBusiness intelligenceGeospatial applicationsMDMNetwork and systems managementProduct catalogueWeb analyticsIndexing your slow RDBMS
  • Social networksRecommendations enginesBusiness intelligenceGeospatial applicationsMDMNetwork and systems managementProduct catalogueWeb analyticsIndexing your slow RDBMS
  • Social networksRecommendations enginesBusiness intelligenceGeospatial applicationsMDMNetwork and systems managementProduct catalogueWeb analyticsIndexing your slow RDBMS
  • Transcript

    • 1. Cédric Fauvet Cedric.fauvet@neotechnology.com Twitter Francophone: @Neo4jFr 1 Confidential - Neo Technology, Inc. New opportunities for connected data : Neo4j the graph database
    • 2. Agenda • The gaph theory • About Neo Technology • Uses cases • Vision du marché • The Neo4j Technology • Cypher the Neo4j’s « SQL »
    • 3. The graph theory An 840 : The horeseman’s problem The Arab mathematician and chess master al-Adli ar-Rumi solved the problem.
    • 4. The graph theory An 1735 The Königsberg’s 7 bridges problem How to pass through the bridges only once ? Leonhard Euler Swiss mathematician
    • 5. The graph theory 2013: Today’s questions • Collaboration • Configuration management • Geo mapping • Molecule’s Interaction (Biology) • Impact analysis • Master Data Management • Product management • Recommendation • Social
    • 6. Agenda • The gaph theory • About Neo Technology • Uses cases • Vision du marché • The Neo4j Technology • Cypher the Neo4j’s « SQL »
    • 7. Neo Technology (Neo4j) Corporate Overview • Neo4j founded 2000 • Headquartered in Palo Alto, California • Engineering headquarter in Malmö, Sweden • Employees based in France, Germany, UK, Sweden, US, and Malaysia • 24/7 support on global basis • 100,000+ users • F500 customers such as Adobe, Cisco, Deutsche Telecom, Telenor, Deutsche Post, SFR, Lockheed Martin, and others • SI partners such as Accenture and dozens of local SI boutiques • Technology partners such as VMware, Informatica and Microsoft • Leader in the Graph Database arena • Mission: Help the world to make sense of data
    • 8. Agenda • The gaph theory • About Neo Technology • Uses cases • Vision du marché • The Neo4j Technology • Cypher the Neo4j’s « SQL »
    • 9. Société - Worldwide company - 45 millions users, + 30 000 each days. - Owner of the social networks ApnaCircle (Inde) and Tianji (Chine) Problème Viadeo, integrated Neo4j as their backend database, to store all of their users and relationships. When their network expanded to a level that their traditional MySQL database couldn’t handle, Viadeo experienced performance and storage issues that would not perform at the rate the company was growing. Etude de cas: Réseau social Bénéfices & time frame - Real time recomendation with Neo4j. - Project timeframe = 8 weeks Solution Integrating Neo4j, Viadeo has highly accelerated their system in two ways. Neo4j increased Viadeo’s performance by requiring less storage space andless time to restructure the graph.
    • 10. 10 Company - Worldwide leader in networking for the Internet Solution - Clustered Neo4j Enterprise architecture - Part of a larger infrastructure solution - Multi-region AWS deployment - Neo4j selected in competition with custom solution and Oracle Benefits & time frame - Highly flexible data analysis - Sub-second results for large, densely-connected datasets - User experience - competitive advantage - 12 month project Problem definition - Massive amounts of data tied to members, user groups, member content, etc. all interconnected - Need to infer collaborative relationships based on user-generated content Case study: Web/ISV - social collaboration Adobe
    • 11. 11 Company - Leading telco provider in the Nordics Solution - Neo4j Enterprise solution - Embedded + HA - Replacing 10 yr-old Oracle, Berkeley DB and a mainframe environment Problem definition - Need: Reliable access control administration system for 5mio customers, subscriptions and agreements - Complex dependencies between groups, companies, individuals, accounts, products, subscriptions, services and agreements - Broad and deep graphs (master customers with 1000s of customers, subscriptions & agreements) Case study: Telco Telenor Benefits & time frame - Flexible and dynamic architecture - Exceptional performance -Low cost compared to alternatives -Extensible data model supports new applications and features
    • 12. 12 Company -World wide leader in network infrastructure -Large sales organization Solution -2x Highly Available Neo4j clusters -One live cluster and one backup / hot spare cluster at a different datacenter -Total: 6 Embedded Enterprise Neo4j DBs Benefits & timeframe -Real time overview of sales accounts and owners -The ability to model complex rules for account ownership -Direct commissioning computation through the entire sales organization ->12 month development and rollout Problem definition -Intricate rules governing ownership of sales accounts -Complex rules for sales commissions -Queries complicated to structure with RDBMS -Oracle performance not good enough for online account management Case study: Sales account management Cisco
    • 13. Use case – What’s in common ? Alice ACME ACME EMEA Bob Retail Co. FooBar Inc. Sales Rep Sales Rep Worked For Worked For Sold To
    • 14. Use case – What’s a best path ? Retail Co. Bob ACME Steve Jane Liza Pauline William Sales Rep VP CMO Sales Rep VP
    • 15. Use case : Pattern matching Fraud detection
    • 16. Correspondance Fraud detection
    • 17. Pas de correspondance Fraud detection
    • 18. Graph navigation Impact analysis
    • 19. Start node Impact analysis
    • 20. Follow the relationships Impact analysis
    • 21. Evaluate each node Impact analysis
    • 22. Agenda • The gaph theory • About Neo Technology • Uses cases • Vision du marché • The Neo4j Technology • Cypher the Neo4j’s « SQL »
    • 23. Trend 1:Exponential growth of data 0 250 500 750 1000 2007 2008 2009 2010 Exabytes of new unique digital information
    • 24. size * connectivity = complexity
    • 25. Agenda • The gaph theory • About Neo Technology • Uses cases • Vision du marché • The Neo4j Technology • Cypher the Neo4j’s « SQL »
    • 26. Neo4j Tackles complex data: – Large – Densely-connected – Semi-structured
    • 27. Neo4j characteristics • Fully ACID – Including XA-compliant distributed two-phase commits • High Availability / Read Scaling through master-slave replication with master failover • In-memory speeds with warm caches while maintaining full ACID • Cypher query language and Java APIs
    • 28. Caractéristiques de Neo4j • Transactions Full ACID – XA-compliant distributed two-phase commits • Haute disponibilité / Scalabilité* – master-slave réplication avec master Fail-over – * Lecture • Hautes performance en mémoire – Caches évolués full ACID • Langage des requêtes – Cypher – Java APIs – JDBC – Rest API – Ruby
    • 29. Agenda • The gaph theory • About Neo Technology • Uses cases • Vision du marché • The Neo4j Technology • Cypher the Neo4j’s « SQL »
    • 30. () --> () Cypher the Neo4j’s « SQL » Based on ACSII-Art
    • 31. (A) --> (B) A B Cypher the Neo4j’s « SQL » Each node have a identifier
    • 32. A -[:LOVES]-> B LOVES A B Cypher the Neo4j’s « SQL » Relationship
    • 33. A --> B --> C A B C Cypher the Neo4j’s « SQL » You can traverse the graph
    • 34. A -[*]-> B A B A B A B Cypher the Neo4j’s « SQL » You can dynamically traverse the graph
    • 35. Cypher the Neo4j’s « SQL » The friend of friend query START john=node:node_auto_index(name = 'John') MATCH john-[:friend]->()-[:friend]->fof RETURN john, fof
    • 36. Thank you Let’s move forward together ! Cédric Fauvet Your contact in France and switzerland E-mail : Cedric.fauvet@neotechnology.com French speaking Twitter : @Neo4jFr French speaking community : meetup.com/graphdb-france

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