![What is a
Graph Database
A graph database is an online (“real-time”)
database management system with CRUD
methods that expose a graph data model
• Two important properties:
• Native graph processing, including
index-free adjacency1 to facilitate traversals
• Native graph storage engine, i.e.
written from the ground up to be
optimized for managing graph data
1] See Rodriguez, M.A., Neubauer, P., ,“The Graph Traversal Pattern,” 2010 (http://arxiv.org/abs/1004.1001)](https://image.slidesharecdn.com/labilinformatiquedecisionnelleetlesgraphes-130503065939-phpapp02/85/La-bi-l-informatique-decisionnelle-et-les-graphes-15-320.jpg)
![Overview of Popular
Graph Data Models
• Property Graph
• Description: A “directed, labeled, attributed, multi-
graph”1 which exposes three building blocks: nodes, typed
relationships and key-value properties on both nodes and
relationships
• Vendors: Neo4j, OrientDB, InfiniteGraph, Dex
• RDF Triples
• Description: URI-centered subject-predicate-object
triples as pioneered by the semantic web movement2
• Vendors: AllegroGraph, Sesame
• HyperGraph
• Description: A generalized graph where a relationship
can connect an arbitrary amount of nodes (compared to
the more common binary graph models)3
• Vendors: HyperGraphDB,TrinityDB
1] Rodriguez, M.A., Neubauer, P., “Constructions from Dots and Lines,” 2010, http://arxiv.org/abs/1006.2361
2] W3C,“The Resource Description Framework (RDF),” 2004, http://www.w3.org/RDF/
3] Wikipedia, http://en.wikipedia.org/wiki/Hypergraph](https://image.slidesharecdn.com/labilinformatiquedecisionnelleetlesgraphes-130503065939-phpapp02/85/La-bi-l-informatique-decisionnelle-et-les-graphes-16-320.jpg)
![Neo Technology, Inc Confidential
What the Cypher Query Looks Like:
What sushi restaurants in NYC do my friends like?
START me=node:person(name = 'Philip'),
location=node:location(location='New York'),
cuisine=node:cuisine(cuisine='Sushi')
MATCH (me)-[:IS_FRIEND_OF]->(friend)-[:LIKES]->(restaurant)
-[:LOCATED_IN]->(location),(restaurant)-[:SERVES]->(cuisine)
RETURN restaurant](https://image.slidesharecdn.com/labilinformatiquedecisionnelleetlesgraphes-130503065939-phpapp02/85/La-bi-l-informatique-decisionnelle-et-les-graphes-22-320.jpg)
La bi, l'informatique décisionnelle et les graphes
- 1. Neo Technology, Inc Confidential La BI, l'informatique décisionnelle et les graphes Philip Rathle, Sr Dir Products [email protected] http://twitter.com/prathle
- 2. Neo Technology, Inc Confidential Les Graphes et la Pensée
- 3. Neo Technology, Inc Confidential The Brain Structure: Neurons Connected by Synapses. Processing: Signals Relayed Between Neurons through Synapses
- 4. Neo Technology, Inc Confidential Human Thinking Structured Unstructured (Creative) Both forms involve processing connections
- 5. Neo Technology, Inc Confidential Les Applications Graphes dans le Commerce
- 6. Neo Technology, Inc Confidential Early Adopters of Graph Tech
- 7. Neo Technology, Inc Confidential Evolution of Web Search Survival of the Fittest Pre-1999 WWW Indexing Discrete Data 1999 - 2012 Google Invents PageRank Connected Data (Simple) 2012-? Google Knowledge Graph, Facebook Graph Search Connected Data (Rich)
- 8. Neo Technology, Inc Confidential Evolution of Online Recruiting 2010-11 Resume Searching & Scoring Aggregated Data Survival of the Fittest 2011-12 Social Job Search Connected Data
- 9. Neo Technology, Inc Confidential Consumer Web Giants Depends on Five Graphs Gartner’s “5 Graphs” Social Graph Ref: http://www.gartner.com/id=2081316 Interest Graph Payment Graph Intent Graph Mobile Graph
- 10. Neo Technology, Inc Confidential Graph Buzz!
- 11. Neo Technology, Inc Confidential Core Industries & Use Cases: Web / ISV Finance & Insurance Communi- cations Logistics Life Sciences Media & Publishing Education, Not-for- Profit Government, Aerospace, Gaming, Other Network Management MDM Social Geo Authorization & Access Control Content Management Recommend- ations Fraud Detection, Other Accenture Select Commercial Customers (Community Users Not Included) Neo4j Adoption Snapshot*
- 12. Neo Technology, Inc Confidential Ecosystème de la Technologie Graph
- 13. Neo Technology, Inc Confidential Data Storage & Processing • Graph Databases • Graph Compute Engines Programming: • Graph-Centric APIs & Languages • Graph Algorithms Tools: • Visualization Tools & Libraries • Other Key Graph Analytic Technologies
- 14. Neo Technology, Inc Confidential Typical Graph BI Environment Application Other Databases ETL Neo4j Cluster Data Storage & Business Rules Execution Reporting Graph- Dashboards & Ad-hoc Analysis Graph Visualization End User Ad-hoc visual navigation & discovery Bulk Analytic Infrastructure (e.g. Graph Compute Engine) ETL Graph Mining & Aggregation Data Scientist Ad-Hoc Analysis
- 15. What is a Graph Database A graph database is an online (“real-time”) database management system with CRUD methods that expose a graph data model • Two important properties: • Native graph processing, including index-free adjacency1 to facilitate traversals • Native graph storage engine, i.e. written from the ground up to be optimized for managing graph data 1] See Rodriguez, M.A., Neubauer, P., ,“The Graph Traversal Pattern,” 2010 (http://arxiv.org/abs/1004.1001)
- 16. Overview of Popular Graph Data Models • Property Graph • Description: A “directed, labeled, attributed, multi- graph”1 which exposes three building blocks: nodes, typed relationships and key-value properties on both nodes and relationships • Vendors: Neo4j, OrientDB, InfiniteGraph, Dex • RDF Triples • Description: URI-centered subject-predicate-object triples as pioneered by the semantic web movement2 • Vendors: AllegroGraph, Sesame • HyperGraph • Description: A generalized graph where a relationship can connect an arbitrary amount of nodes (compared to the more common binary graph models)3 • Vendors: HyperGraphDB,TrinityDB 1] Rodriguez, M.A., Neubauer, P., “Constructions from Dots and Lines,” 2010, http://arxiv.org/abs/1006.2361 2] W3C,“The Resource Description Framework (RDF),” 2004, http://www.w3.org/RDF/ 3] Wikipedia, http://en.wikipedia.org/wiki/Hypergraph
- 17. Graph Compute Engine Processing platforms that enable graph global computational algorithms to be run against large data sets Graph Mining Engine (Working Storage) In-Memory Processing System(s) of Record Graph Compute Engine Data extraction, transformation, and load
- 18. Neo Technology, Inc Confidential Graph Global Queries What is the max/min/avg. number of connections per node? (aka “Degree Distribution”)
- 19. Neo Technology, Inc Confidential Quoi faire avec un Graph Database? Example: Facebook Graph Search
- 20. Neo Technology, Inc Confidential For the Facebook Graph Question: What sushi restaurants in NYC do my friends like?
- 21. Neo Technology, Inc Confidential What the Graph Looks Like: What sushi restaurants in NYC do my friends like?
- 22. Neo Technology, Inc Confidential What the Cypher Query Looks Like: What sushi restaurants in NYC do my friends like? START me=node:person(name = 'Philip'), location=node:location(location='New York'), cuisine=node:cuisine(cuisine='Sushi') MATCH (me)-[:IS_FRIEND_OF]->(friend)-[:LIKES]->(restaurant) -[:LOCATED_IN]->(location),(restaurant)-[:SERVES]->(cuisine) RETURN restaurant
- 23. Neo Technology, Inc Confidential What the Search Looks Like: What sushi restaurants in NYC do my friends like?
- 24. Neo Technology, Inc Confidential What Other Graph Searches Look Like What drugs will bind to protein X and not interact with drugY?
- 25. Neo Technology, Inc Confidential Graph Dashboards
- 27. Fraud Detection & Money Laundering
- 28. Service Assurance & Network Failure Analysis
- 29. Neo Technology, Inc Confidential Industry Example: 5 Graphs of Communications
- 30. Neo Technology, Inc Confidential #1:The Network Graph Graphs in Communications Cell Signal Analysis Router Service DEPENDS_O N Switch Switch Router Fiber Link Fiber Link Fiber Link Oceanfloor Cable DEPENDS_ON DEPENDS_ON DEPEN DS_O N DEPENDS_ON DEPENDS_ON DEPENDS_ON DEPENDS_ON DEPENDS_ON DEPENDS_ON LINKED LINKED LIN KED DEPENDS_ON “What if” Downtime Analysis (Service-to-Infrastructure Mapping) Network Inventory & Cost Accounting
- 31. Neo Technology, Inc Confidential #2:The Social Graph Graphs in Communications Mobile apps, Collaboration, Social Recommendations, and more...
- 32. Neo Technology, Inc Confidential #3:The Call Graph Graphs in Communications Plan & Feature Recommendations,Assess Churn Risk
- 33. Neo Technology, Inc Confidential #4: Master Data Graph Graphs in Communications Organizational Hierarchy Management Resource Authorization Ref: http://www.slideshare.net/verheughe/how-nosql-paid-off-for-telenor
- 34. Neo Technology, Inc Confidential #5:The Help Desk Graph Graphs in Communications Online Recommendations for Case Avoidance
- 35. Neo Technology, Inc Confidential Entitlements & Identity Management Network Asset Management Network Cell Analysis Geo Routing (Public Transport) BioInformatics Emergent Graph in Other Industries (Actual Neo4j Graphs) Insurance Risk Analysis
- 36. Neo Technology, Inc Confidential Web Browsing Portfolio Analytics Mobile Social ApplicationGene Sequencing Emergent Graph in Other Industries (Actual Neo4j Graphs)
- 37. Neo Technology, Inc Confidential Cas d’études selectionés
- 38. Neo Technology, Inc Confidential Background • World’s largest provider of IT infrastructure, software & services • HP’s Unified Correlation Analyzer (UCA) application is a key application inside HP’s OSS Assurance portfolio • Carrier-class resource & service management, problem determination, root cause & service impact analysis • Helps communications operators manage large, complex and fast changing networks Business problem • Use network topology information to identify root problems causes on the network • Simplify alarm handling by human operators • Automate handling of certain types of alarms Help operators respond rapidly to network issues • Filter/group/eliminate redundant Network Management System alarms by event correlation Solution & Benefits • Accelerated product development time • Extremely fast querying of network topology • Graph representation a perfect domain fit • 24x7 carrier-grade reliability with Neo4j HA clustering • Met objective in under 6 months Industry: Web/ISV, Communications Use case: Network Management Global (U.S., France)
- 39. Neo Technology, Inc Confidential Background •One of the world’s largest logistics carriers •Projected to outgrow capacity of old system •New parcel routing system •Single source of truth for entire network •B2C & B2B parcel tracking •Real-time routing: up to 5M parcels per day Business problem •24x7 availability, year round •Peak loads of 2500+ 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 & Benefits •Neo4j provides the ideal domain fit: •a logistics network is a graph •Extreme availability & performance with Neo4j clustering •Hugely simplified queries, vs. relational for complex routing •Flexible data model can reflect real-world data variance much better than relational •“Whiteboard friendly” model easy to understand Industry: Logistics Use case: Parcel Routing
- 40. Neo Technology, Inc Confidential Industry: Online Job Search Use case: Social / Recommendations • Online jobs and career community, providing anonymized inside information to job seekers Business problem • Wanted to leverage known fact that most jobs are found through personal & professional connections • Needed to rely on an existing source of social network data. Facebook was the ideal choice. • End users needed to get instant gratification • Aiming to have the best job search service, in a very competitive market Solution & Benefits • First-to-market with a product that let users find jobs through their network of Facebook friends • Job recommendations served real-time from Neo4j • Individual Facebook graphs imported real-time into Neo4j • Glassdoor now stores > 50% of the entire Facebook social graph • Neo4j cluster has grown seamlessly, with new instances being brought online as graph size and load have increased Person Company KNOW S Person Person KNOWS Company KNOWS WORKS_AT WORKS_AT Neo Technology Confidential Background Sausalito, CA
- 41. Neo Technology, Inc Confidential Industry: Communications Use case: Recommendations •Cisco.com serves customer and business customers with Support Services •Needed real-time recommendations, to encourage use of online knowledge base •Cisco had been successfully using Neo4j for its internal master data management solution. •Identified a strong fit for online recommendations Solution & Benefits •Cases, solutions, articles, etc. continuously scraped for cross-reference links, and represented in Neo4j •Real-time reading recommendations via Neo4j •Neo4j Enterprise with HA cluster •The result: customers obtain help faster, with decreased reliance on customer support Neo Technology Confidential Background Business problem •Call center volumes needed to be lowered by improving the efficacy of online self service •Leverage large amounts of knowledge stored in service cases, solutions, articles, forums, etc. •Problem resolution times, as well as support costs, needed to be lowered Support Case Support Case Knowledge Base Article Solution Knowledge Base Article Knowledge Base Article Message San Jose, CA Cisco.com
- 42. Neo Technology, Inc Confidential Interactive Television Programming Industry: Communications Use case: Social gaming Background • Europe’s largest communications company • Provider of mobile & land telephone lines to consumers and businesses, as well as internet services, television, and other services Solution & Benefits • Interactive, social offering gives fans a way to experience the game more closely • Increased customer stickiness for Deutsche Telekom • A completely new channel for reaching customers with information, promotions, and ads • Clear competitive advantage Frankfurt, Germany Business problem • The Fanorakel application allows fans to have an interactive experience while watching sports • Fans can vote for referee decisions and interact with other fans watching the game • Highly connected dataset with real-time updates • Queries need to be served real-time on rapidly changing data • One technical challenge is to handle the very high spikes of activity during popular games
- 43. Neo Technology, Inc Confidential Reasons for Choosing a Graph Database 1. Order-of-magnitude improvements in query performance for complex, connected data 2. Drastically accelerated application development cycles 3. Maintainability and extensibility of the data model 4. Maturity and reliability of the product
- 44. Neo Technology, Inc Confidential Questions ?
- 45. Neo Technology, Inc Confidential Merci ! Pour aller plus loin : Cédric Fauvet – Votre contact en France E-‐mail : [email protected] Twi+er : @Neo4jFr Communauté Francophone : meetup.com/graphdb-‐france