Neo4j - 5 cool graph examples
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This document discusses graph databases and provides examples of how the Neo4j graph database can be used. It shows how Neo4j supports social, spatial, financial and other types of connected data. It also summarizes Neo4j's REST API, support for object-oriented programming, routing algorithms, multiple indexes, recommendation systems, and other use cases. The document advocates for graph databases for any problem involving multiple relationships and connections between entities.
Neo4j - 5 cool graph examples
- 1. Neo4j And some graph problems #neo4j Peter Neubauer @peterneubauer COO, Neo Technology peter@neotechnology.com
- 2. Any sufficiently advanced technology is indistinguishable from magic. Arthur C. Clarke @kymerawand
- 3. First, a recap: NOSQL data models Key-value stores Data size Column Family Document databases Graph databases We are here Data complexity
- 4. What makes a good DB? Separate Logic and Data Support Ad-Hoc queries Be persistent Scale good enough
- 5. The property graph model Core abstractions: name = “Emil” Nodes age = 29 sex = “yes” Relationships between nodes Properties on both 1 2 Traversal framework type = KNOWS High performance time = 4 years 3 queries on connected data sets type = car vendor = “SAAB” Other bindings model = “95 Aero” Langs, REST, Gremlin, RDF
- 6. Social data (customer: brand-name social network) name = “Marcy Runkle” name = “Hank” last_name = “Moody” name = “Mike” age = 42 42 age = 29 S W NO disclosure = public K KNOWS KNOWS KNO 1 7 3 W S KN 13 S OW name = “Charlie” KNOW S last_name = “Runkle” name = “Dani” last_name = “California” age = 3 days age = 27 2 name = “Karen”
- 7. Just a social graph?
- 8. Spatial data (customer: large telecom company) name = ... name = “The Tavern” lat = 1295238237 name = “Omni Hotel” long = 234823492 42 lat = 3492848 long = 283823423 length = 7 miles AD RO ROAD ROAD ROO 1 7 3 OAD RO 13 AD name = ... ROAD lat, long = ... name = “Swedland” lat = 23410349 length = 3 miles long = 2342348852 2 name = ...
- 9. Social? Spatial? … Social AND spatial!
- 10. Social AND spatial data (customer: LBS) name = “Peter” name = “The Tavern” lat = 1295238237 name = “Omni Hotel” long = 234823492 42 lat = 3492848 S W NO long = 283823423 weight = 10 K ROAD LIKES SIBL 1 7 3 IN G RO 13 AD name = “Emil” ROAD beer_qual = expert name = “Maria” age = 30 length = 3 miles beer_qual = non-existant 2 name = ...
- 11. Financial data (customer: international bank) name = ... name = “The Tavern” lat = 1295238237 long = 234823492 42 name = “Mr Godfather” AW karma = veeeery-low HDR cash = more-than-you amount = $1000 IT W OWNS TRANSFER WIT 1 7 3 HDR AW 13 S FE R DE name = “Emil” P OS cash = always-too-li'l IT TRAN title = “ATM @ Wall St” id = 230918484233 amount = $1000 cash_left = 384204 2 name = ...
- 12. Use Cases REST in Neo4j The graph as an OODB – Roo, Grails Jruby, Jo4neo Deep graph algos – Routing with A* Multiple indexes in the graph – GIS Recommendation systems – Gremlin and LinkedData
- 13. REST in Neo4j Build on self describing JSON Indexing Querying Bindings to PHP, C#, JS OpenGraph API Jruby, Scala
- 14. The Graph for objects Keep data clean! Annotation based Grails Jo4neo Roo JPA Mixin based Django JRuby C# (REST) PHP (REST)
- 15. The Graph as an OODB
- 16. Routing with Neo4j and A*
- 17. Routing with Neo4j and A*
- 18. Multiple indexes - GIS QuadTree (2D) Hierarchy Time (1D) On-demand index
- 19. Multiple indexes - GIS
- 20. Multiple indexes - GIS
- 21. Recommendation - Gremlin gremlin.tinkerpop.com XPath based “Perl for Graphs” Property Graph Model Neo4j, RDF-SAIL, Tinkergraph, MongoDB, FS LinkedData SAIL
- 24. Other use cases Activity streams Process automation Life-filtering of event streams Web-of-Things data f ows l Object oriented reporting Jasper Reports ReportAnywhere Scripting
- 25. Why graph databases? “For anything with multiple relationships, multiple connections N e o4 j ab s ol u t e l y R OCK S!” http://bit.ly/dys4nx A web where the default is social → an explosion of graph-y data “Just 3 years ago, the data sets our product handled were very simple. But the past 9-12 months have seen an e x p l os i on of the number of relationships between things.” Manager of an enterprise product for the Fortune 5000 Werner Vogels CTO, Amazon
- 26. How ego are you? (aka other impls?) Franz’ Al l e g roGrap h (http://agraph.franz.com) Proprietary, Lisp, RDF-oriented but real graphdb Sones g rap h DB (http://sones.com) Proprietary, .NET, in beta Twitter's Fl oc k DB (http://github.com/twitter/flockdb) Twitter's (graph) database for large and shallow graphs Google P re g e l (http://bit.ly/dP9IP) We are oh-so-secret Objectivity's I n fi n i te Gra p h (http://infinitegraph.com) New, closed OODB with Graph Layer on top
- 27. Why Neo4j? Most widely deployed graph db in the world Robust: 24/7 production since 2003 Mature: lots of production deployments Community: ecosystem of tools, bindings, frameworks Available NOW under AGPLv3 / commercial license AGPLv3: “if you’re open source, we’re open source” If you have proprietary software? Must buy a commercial license But the f rst one is free! For ALL use-cases. i Download http://neo4j.org Feedback http://lists.neo4j.org
- 28. Th e N e o4 j te a m i s h i ri n g ! Do you see the Matrix? Apply now.
- 29. Questions? Image credit: lost again! Sorry :(