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Introduction to Neo4j

With the introduction of the Neo4j Graph Platform and increased adoption of graph database technology across all industries, now is a better time than ever to get started with graphs.

Join us for this introduction to Neo4j and graph databases. We'll discuss the primary use cases for graph databases and explore the properties of Neo4j that make those use cases possible.

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Introduction to Neo4j

  1. 1. Neo4j Introduction Jonny Cheetham Neo4j, London
  2. 2. Neo4j is an enterprise-grade native graph platform that enables you to: • Store, reveal and query data relationships • Traverse and analyze any levels of depth in real-time • Add context and connect new data on the fly Who We Are: Leader in Graph Innovations • Performance • ACID Transactions • Schema-free Agility • Graph Algorithms Designed, built and tested natively for graphs from the start for: • Developer Productivity • Hardware Efficiency • Global Scale • Graph Adoption Graph Transactions Graph Analytics Data Integration Development & Admin Analytics Tooling Drivers & APIs Discovery & Visualization 2
  3. 3. 720+ 7/10 12/25 8/10 53K+ 100+ 300+ 450+ Adoption Top Retail Firms Top Financial Firms Top Software Vendors Customers Partners • Creator of the Neo4j Graph Platform • ~250 employees • HQ in Silicon Valley, other offices include London, Munich, Paris and Malmö Sweden • $80M new funding led by Morgan Stanley & One Peak. Total $160M from Fidelity, Sunstone, Conor, Creandum, and Greenbridge Capital • Over 15M+ open source downloads & container pulls • 325+ 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 Neo4j - The Graph Company 3
  4. 4. Networks of People Knows Knows Knows Knows Business Processes Bought Bought Viewed Returned Bought Knowledge Networks Plays Lives_in In_sport Likes Fan_of Plays_for E.g., Risk management, Supply chain, Payments E.g., Employees, Customers, Suppliers, Partners, Influencers E.g., Enterprise content, Domain specific content, eCommerce content Data connections are increasing as rapidly as data volumes The Rise of Connections in Data Electronic Networks On-prem & cloud computing, Cellular, Telco & Internet, IoT 4
  5. 5. 5 Graph Databases are Designed for Connected Data TRADITIONAL DATABASES BIG DATA TECHNOLOGY Store and retrieve data Aggregate and filter data Connections in data Real time storage & retrieval Real-Time Connected Insights Long running queries aggregation & filtering “Our Neo4j solution is literally thousands of times faster than the prior MySQL solution, with queries that require 10-100 times less code” Volker Pacher, Senior Developer Up to 3 Max # of hops 1 Millions
  6. 6. CAR DRIVES name: “Dan” born: May 29, 1970 twitter: “@dan” name: “Ann” born: Dec 5, 1975 since: Jan 10, 2011 brand: “Volvo” model: “V70” Latitude: 37.5629900° Longitude: -122.3255300° Nodes • Can have Labels to classify nodes • Labels have native indexes Relationships • Relate nodes by type and direction Properties • Attributes of Nodes & Relationships • Stored as Name/Value pairs • Can have indexes and composite indexes • Visibility security by user/role Neo4j Invented the Labeled Property Graph Model MARRIED TO LIVES WITH OW NS PERSON PERSON 6
  7. 7. Strictly ConfidentialStrictly Confidential 7 Neo4j Is Helping The World To Make Sense of Data ICIJ used Neo4j to uncover the world’s largest journalistic leak to date, The Panama Papers NASA uses Neo4j for a “Lessons Learned” database to improve effectiveness in search missions in space Neo4j is used to graph the human body, map correlations, identify cause & effect and search for the cure for cancer SAVING DEMOCRACY MISSION TO MARS CURING CANCER
  8. 8. Recommendations Dynamic Pricing IoT-applicationsFraud Detection Real-Time Transaction Applications Generate and Protect Revenue Customer Engagement Metadata and Advanced Analytics Data Lake Integration Knowledge Graphs for AI Risk Mitigation Generate Actionable Insights Network Management Supply Chain Efficiency Identity and Access Management Internal Business Processes Improve Efficiency and Cut Costs 8 Graph Use Cases by Value Proposition
  9. 9. "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 DBMA “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 Analysts See Unique Benefits of Graphs "Neo4j is the clear market leader in the graph space. It has the most users, it uses a widely adopted language that is much easier than Gremlin and in many respects, it has consistently been a lot more innovative than its competitors.” “It is the Oracle or SQL Server of the graph database world.” March, 2019 "Our research suggests that graph databases have the best chance to survive and thrive as a distinct category (versus the other NoSQL models) because connected data applications present serious performance problems that only a specialized graph DB can solve.” March, 2019 9
  10. 10. Graph Platform & Initiatives 10
  11. 11. Graph Transactions Graph Analytics Data Integration Development & Admin Analytics Tooling Drivers & APIs Discovery & Visualization Developers Admins Applications Business Users Data Analysts Data Scientists Enterprise Data Hub Native Graph Platform: Tools for Many Users 11
  12. 12. Collections-Focused Multi-Model, Documents, Columns & Simple Tables, Joins Neo4j is designed for data relationships Different Paradigms NoSQL Relational DBMS Neo4j Graph Platform Connections-Focused Focused on Data Relationships Development Benefits Easy model maintenance Easy query Deployment Benefits Ultra high performance Minimal resource usage 12
  13. 13. 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 13
  14. 14. Graph & ML Algorithms in Neo4j+35 graph-algorithms- book/ Pathfinding & Search Centrality / Importance Community Detection Link Prediction Finds optimal paths or evaluates route availability and quality Determines the importance of distinct nodes in the network Detects group clustering or partition options Evaluates how alike nodes are Estimates the likelihood of nodes forming a future relationship Similarity 14
  15. 15. Neo4j Bloom 15 • Visualize • Communicate • Discover • Navigate • Isolate • Edit • Share
  16. 16. Graph Use Cases 16
  17. 17. 17 Real-Time Recommendations Fraud Detection Network & IT Operations Master Data Management Knowledge Graph Identity & Access Management Common Graph Technology Use Cases AirBnb
  18. 18. Business Problem • Find relationships between people, accounts, shell companies and offshore accounts • Journalists are non-technical • Biggest “Snowden-Style” document leak ever; 11.5 million documents, 2.6TB of data Solution and Benefits • Pulitzer Prize winning investigation resulted in robust coverage of fraud and corruption • PM of Iceland & Pakistan resigned, exposed Putin, Prime Ministers, gangsters, celebrities (Messi) • Led to assassination of journalist in Malta Background • International Consortium of Investigative Journalists (ICIJ), small team of data journalists • International investigative team specializing in cross-border crime, corruption and accountability of power • Works regularly with leaks and large datasets ICIJ Panama Papers INVESTIGATIVE JOURNALISM Fraud Detection / Knowledge Graph18
  20. 20. Bank US Account Person A Company Bank Bahamas Address HAS REGISTERED IS_OFFICER_ OF WITH LIVES_AT LIVES_AT NODE RELATIONSHIP Person B 20
  21. 21. Neo4j Customer Deep Dive 21
  22. 22. 22 • 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
  23. 23. Background • Largest Cable TV & Internet Provider in US • 3rd Largest network on the planet • xFi is consumer experience in 3M houses • Internet, router, devices, security, voice & telephony • Transformational customer experience Business Problem • Integrate all experience in a smart home • Create innovative ideas based on cross-platform and household member preferences • Add integrated value of xFinity triple play & quad- play services (internet, VoIP, cable TV & home security) Solution and Benefits • Custom content per household member • Security reminders (kids are home, garage left open) • Serves millions of households • Makes content recommendations based on occupant, time of day, permissions and preferences • Has Siri-like voice commands COMCAST Xfinity xFi TELECOMMUNICATIONS Smart Home / Internet of Things23 EE Customer since 2016 Q4
  24. 24. Thomson Reuters Graph 24 • Data Fusion for Portfolio Managers • Graph layers
  25. 25. Background • Personal shopping assistant • Converses with buyer via text, picture and voice to provide real-time recommendations • Combines AI and natural language understanding (NLU) in Neo4j Knowledge Graph • First of many apps in eBay's AI Platform Business Problem • Improve personal context in online shopping • Transform buyer-provided context into ideal purchase recommendations over social platforms • "Feels like talking to a friend" Solution and Benefits • 3 developers, 8M nodes, 20M relationships • Needed high-performance traversals to respond to live customer requests • Easy to train new algorithms and grow model • Generating revenue since launch eBay for Google Assistant ONLINE RETAIL Knowledge Graph powers Real-Time Recommendations25 EE Customer since 2016 Q3
  26. 26. Background • Over 7M citizens suffer from Diabetes • Connecting over 400 researchers • Incorporates over 50 databases, 100k’s of Excel workbooks, 30 database of biological samples • Sought to examine disease from as many angles as possible. Business Problem • Genes are connected by proteins or to metabolites, and patients are connected with their diets, etc… • Needed to improve the utilization of immensely technical data • Needed to cater to doctors and researchers with simple navigation, communication and connections of the graph. Solution and Benefits • Dr. Alexander Jarasch, Head of Bioinformatics and Data Management • Scientists can conduct parallel research without asking the same questions or repeating tests • Built views like a liver sample knowledge graph DZD - German Center for Diabetes Research Medical Genomic Research26 EE Customer since 2016 Q4
  27. 27. Thank You 27