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Neo4j GraphTalk Frankfurt - Einführung

Bruno Ungermann
Neo4j GraphTalk Frankfurt

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Neo4j GraphTalk Frankfurt - Einführung

  1. 1. Herzlich Willkommen! 1
  2. 2. Neo4j GraphTalks DSGVO & Compliance • Einführung in Graphdatenbanken und Neo4j (9.30-10.00) Bruno Ungermann • Strategische Vorteile von DSGVO durch Nutzen von verbundenen Daten (10.00-11.00) Stefan Kolmar • Wie werden Graphdatenbank-Projekte mit Neo4j zum Erfolg? (11.00-11.30) Stefan Kolmar • Q&A
  3. 3. Complexity
  4. 4. The Internet (of Things)
  5. 5. Domain Model Logistics Process
  6. 6. Traditional Approach: Fixed Schema, Tables
  7. 7. Graph Model: Nodes & Relationships Container Load USING ROUTE Depart 2014-04-15 Arrive 2014-04-28 USING_CARRIER Vessel Physical Container Shipment Carrier Emission Class A Shipment: ID 256787 Carrier: DHL Route 10520km Route: 823km Fueling Max Wgt 80 Type Gas B Town: Tokyo Town: Hong Kong Town: Hamburg Container LoadContainer LoadContainer Load Parcel Weight 15.5kg Container Load
  8. 8. Intuitiveness
  9. 9. Flexibility
  10. 10. Flexibility & Agility
  11. 11. “We found Neo4j to 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
  12. 12. Neo4j - The Graph Company 500+ 7/10 12/25 8/10 53K+ 100+ 250+ 450+ Adoption Top Retail Firms Top Financial Firms Top Software Vendors Customers Partners • Creator of the Neo4j Graph Platform • ~200 employees • HQ in Silicon Valley, other offices include London, Munich, Paris and Malmö (Sweden) • $80M in funding from Fidelity, Sunstone, Conor, Creandum, and Greenbridge Capital • Over 10M+ downloads, • 250+ enterprise subscription customers with over half with >$1B in revenue Ecosystem Startups in program Enterprise customers Partners Meet up members Events per year Industry’s Largest Dedicated Investment in Graphs
  13. 13. 2010 2011 2012 2013 2015 2017 Invented Cypher - Leading language for graph queries First open source GA version of a property graph database O’Reilly Graph Database — first definitive book for graph professionals Introduced labels to simplify graph modeling openCypher Project — open sourced Cypher to create the de facto standard Launched industry’s first Graph Platform Neo4j — The Graph Technology Pioneer 2014 Visual Graph Query Browser 2016 Causal Consistency for Graphs
  14. 14. 2012  2018 May 10th-11th, London CONFERENCE + TRAINING
  15. 15. "Neo4j continues to dominate the graph database market.” “69% of enterprises have, or are planning to implement graphs over next 12 months” October, 2017 “The most widely stated reason in the survey for selecting Neo4j was to drive innovation” February, 2018 Critical Capabilities for DBMSA “In fact, the rapid rise of Neo4j and other graph technologies may signal that data connectedness is indeed a separate paradigm from the model consolidation happening across the rest of the NoSQL landscape.” March, 2018 Graph is a Unique Paradigm
  16. 16. Graph Based Success
  17. 17. 17 • Record “Cyber Monday” sales • About 35M daily transactions • Each transaction is 3-22 hops • Queries executed in 4ms or less • Replaced IBM Websphere commerce • 300M pricing operations per day • 10x transaction throughput on half the hardware compared to Oracle • Replaced Oracle database • Large postal service with over 500k employees • Neo4j routes 7M+ packages daily at peak, with peaks of 5,000+ routing operations per second. Handling Large Graph Work Loads for Enterprises Real-time promotion recommendations Marriott’s Real-time Pricing Engine Handling Package Routing in Real-Time
  18. 18. Discrete Data Minimally connected data 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
  19. 19. Graph Transactions Graph Analytics Data Integration Development & Admin Analytics Tooling Drivers & APIs Discovery & Visualization Developers Admins Applications Business Users Data Analysts Data Scientists
  20. 20. Neo4j Bloom Features 20 • Prompted Search • Property Browser & editor • Category icons and color scheme • Pan, Zoom & Select
  21. 21. How Neo4j Fits — Common Architecture Patterns From Disparate Silos To Cross-Silo Connections From Tabular Data To Connected Data From Data Lake Analytics to Real-Time Operations
  22. 22. 22 Real-Time Recommendations Fraud Detection Network & IT Operations Master Data Management Knowledge Graph Identity & Access Management Common Graph Technology Use Cases AirBnb
  23. 23. Background • Panama based lawyers 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/Paradise Papers Fraud Detection23
  24. 24. Herausforderungen DSGVO
  25. 25. Nachverfolgung personenbezogener Daten
  26. 26. Vorteile Graphtechnologie für DSGVO
  27. 27. In vier Schritten zur DSGVO-Compliance
  28. 28. How to Start
  29. 29. Whiteboard Session
  30. 30. Bootcamp