Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Neo4j GraphTalk Florence - Introduction to the Neo4j Graph Platform

Neo4j GraphTalk Florence
Bill Brooks, Neo4j

  • Login to see the comments

  • Be the first to like this

Neo4j GraphTalk Florence - Introduction to the Neo4j Graph Platform

  1. 1. Welcome to GraphTalk Florence Neo4j – The Graph Platform Bill Brooks Territory Manager, South Europe Neo4j
  2. 2. Connectedness Represented in Graphs C C A AA U S S SS S USER_ACCESS CONTROLLED_BY SUBSCRIBED _BY User Customers Accounts Subscriptions VP Staff Staff StaffStaff DirectorStaffDirector Manager Manager Manager Manager Fiber Link Fiber Link Fiber Link Ocean Cable Switch Switch Router Router Service Organizational Hierarchy Product Subscriptions Network Operations Social Networks
  3. 3. Static world Connected World Native Graph Database Static World vs Connected World
  4. 4. CONSUMER DATA PRODUCT DATA PAYMENT DATA SOCIAL DATA SUPPLIER DATA The next wave of competitive advantage will be all about using connections to identify and build knowledge Graphs in The Age of Connections
  5. 5. Graph Transformation Maturity Context Paths Auto-Graphs Graph Layers 1st Graph Cross-Connect Cross-tech applications Internet of Things operations Transparent Neural Networks Blockchain-managed systems Adjacent graph layers inspire new innovations Metadata / Risk Management Knowledge Graphs AI- Powered Customer Experiences Connect unlike objects such as people to products, locations Mobile app explosion Recommendation engines Fraud detectors Desire for more context to follow connections Connects like objects People, computer networks, telco, etc
  6. 6. Density Drives Value In Graphs Metcalfe’s Law of the Network (V=n2) 5 hops < less Value 100’s of hops deliver immense VALUE
  7. 7. Neo4j Solves Connected, Real-Time Problems Connectedness Batch-Precompute Real-Time Data Information Knowledge Insight Wisdom Latency & Freshness
  8. 8. Harnessing Connections Drives Business Value Enhanced Decision Making Hyper Personalization Massive Data Integration Data Driven Discovery & Innovation Product Recommendations Personalized Health Care Media and Advertising Fraud Prevention Network Analysis Law Enforcement Drug Discovery Intelligence and Crime Detection Product & Process Innovation 360 view of customer Compliance Optimize Operations Connected Data at the Center AI & Machine Learning Price optimization Product Recommendations Resource allocation Digital Transformation Megatrends
  9. 9. Who We Are: Neo4j - The Graph Platform 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 • Performance • ACID Transactions • Agility • Graph Algorithms Designed, built and tested natively for graphs from the start for: • Developer Productivity • Hardware Efficiency • Global Scale • Graph Adoption
  10. 10. 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 Neo4j - The Graph Company Ecosystem Startups in program Enterprise customers Partners Meet up members Events per year Industry’s Largest Dedicated Investment in Graphs
  11. 11. Real-Time Recommendations Fraud Detection Network & IT Operations Master Data Management Knowledge Graph Identity & Access Management Common Graph Technology Use Cases AirBnb
  12. 12. Software Financial Services Telecom Retail & Consumer Goods Media & Entertainment Other Industries Airbus Over 250 Enterprises and 10s of Thousands of Projects on Neo4j
  13. 13. 10M+ Downloads 3M+ from Neo4j Distribution 7M+ from Docker Events 400+ Approximate Number of Neo4j Events per Year 50k+ Meetups Number of Meetup Members Globally Largest pool of graph technologists 50k+ Trained/certified Neo4j professionals Trained Developers
  14. 14. 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
  15. 15. "Neo4j continues to dominate the graph database market.” October, 2017 “Customers choose Neo4j to drive innovation.” February, 2018 “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. 2010 2011 2012 2013 2015 2017 Frustrated with Gremlin, Neo 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 open sourced Cypher query language as de facto standard Industry’s 1st Graph Platform Graph Algorithms for data scientists Developer’s Neo4j Desktop 2014 Visual Graph Query Browser 2016 Causal Consistency for Graphs Neo4j—The Graph Innovator 2018 2019 Morpheus Graph is a unique paradigm Neo4j Cloud Neo4j Cloud EAP Neo4j Bloom visual discovery Cypher for Apache Spark Cypher for Gremlin GQL Manifesto
  17. 17. CAR 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 PERSON PERSON
  18. 18. Cypher: Powerful and Expressive Query Language MATCH (:Person { name:“Dan”} ) -[:MARRIED_TO]-> (spouse) MARRIED_TO Dan Ann NODE RELATIONSHIP TYPE LABEL PROPERTY VARIABLE
  19. 19. Why Cypher is Better Ease of use drives adoption & popularity • Demonstrable maturity and proven success • Huge ecosystem and support network • Visibly represents relationships & paths • Declarative language is easy to learn Cypher is Open, Easy and Everywhere Cypher on Apache Spark (CAPS) Cypher ToolingBI Tools Integration Tools Cypher on … Additional Sources Apache Hadoop Accelerating Market Adoption • openCypher participation is growing • Reference model for ISO, other research projects • SQL compatible and complementary • Released for under friendly Apache license Evolving and Expanding Rapidly Incorporating new ideas for Cypher such as: • Return results as graphs OR tables of data (composability) • compose subqueries and chain-linking query algorithms • build graph expressions • define new graph object types like walks, runs and paths
  20. 20. Graph Platform: Connects to Many Roles in Enterprise DEVELOPERS ADMINS Graph Analytics Graph Transactions DATA ANALYSTS DATA SCIENTISTS APPLICATIONS Drivers & APIs Data Integration BIG DATA IT Analytics Tooling BUSINESS USERS Discovery & Visualization Development & Administration
  21. 21. Optimized Algorithms Robust Procedures Connections- First Query Language Native Graph Database Analytics Tooling Neo4j Graph Platform: Analytics
  22. 22. Neo4j Graph Algorithms Finds the shortest path or evaluates route availability and quality Evaluates how a group is clustered or partitioned Determines the importance of distinct nodes in the network
  23. 23. • Operational workloads • Analytics workloads Real-time Transactional and Analytic Processing • Interactive graph exploration • Graph representation of data Discovery and Visualization • Native property graph model • Dynamic schema Agility • Cypher - Declarative query language • Procedural language extensions • Worldwide developer community Developer Productivity • 10x less CPU with index-free adjacency • 10x less hardware than other platforms Hardware efficiency Neo4j: Graph Platform Benefits Performance • Index-free adjacency • Millions of hops per second
  24. 24. Connecting Roles & Projects around Enterprise Data Hub Data Scientists Real-time Graph traversal Applications Developers & Prod Mgrs Analysts and Business Users Chief Officers of … Compliance, Data, Digital, Information, Innovation, Marketing, Operations, Risk & Security… Big Data IT & Architecture ID, Auth & Security Network & IT Ops Metadata Management 360⁰ Marketing Customer 360 Real-time Cybersecurity Account navigation • Multiple paths through organization • Graphs have strong appetite for data to add nodes & increase density of relationships • Value of graph increase according to Metcalfe’s Law (V=n2) • Customer applications iterate every 3 months
  25. 25. 1 2 3 4 5 6 Key Architecture Components
  26. 26. 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
  27. 27. Development & Administration Analytics Tooling Graph Analytics Graph Transactions Data Integration Discovery & VisualizationDrivers & APIs AI Neo4j Database 3.4 • 70% faster Cypher • Native String Indexes (up to 5x faster writes) • 100B+ bulk importer Improved Admin Experience • Rolling upgrades • 2x faster backups • Cache Warming on startup • Improved diagnostics Morpheus for Apache Spark • Graph analytics in the data lake • In-memory Spark graphs from Apache Hadoop, Hive, Gremlin and Spark • Save graphs into Neo4j • High-speed data exchange between Neo4j & data lake • Progressive analysis using named graphs Graph Data Science • High speed graph algorithms Neo4j Bloom • New graph illustration and communication tool for non- technical users • Explore and edit graph • Search-based • Create storyboards • Foundation for graph data discovery • Integrated with graph platform Multi-Cluster routing built into Bolt drivers • Date/Time data type • 3-D Geospatial search • Secure, Horizontal Multi-Clustering • Property-value Security The Neo4j Graph Platform, Summer 2018
  28. 28. Neo4j Bloom Features 28 • Prompted Search • Property Browser & editor • Category icons and color scheme • Pan, Zoom & Select
  29. 29. Different Data Types Morph Tables into Graphs, Graphs into Tables Morpheus for Apache Spark: Future: Any Kettle Source RDBMS & JSON Future: Other Graph Data Sources
  30. 30. Thank you Bill Brooks Territory Manager, South Europe Neo4j