Exploing	  Big	  Data	  with	  Graphs	  Rik	  Van	  Bruggen	  Regional	  Director,	  Neo	  Technology	  @rvanbruggen	  
Roadmap	  •  The	  Relaonal	  Crossroads	  •  The	  NOSQL	  answer	  – The	  volume	  answer	  – The	  complexity	  answer...
The	  	  “Big	  Data”	  problem	  The	  	  big	  	  “Data	  Problem”	  
NOT	  ONLY	  SQL	  
The	  	  “Big	  Data”	  problem	  
hLp://www.flickr.com/photos/crazyneighborlady/355232758/	  
hLp://gallery.nen.gov.uk/image82582-­‐.html	  
hLp://www.xtranormal.com/watch/6995033/mongo-­‐db-­‐is-­‐web-­‐scale	  
Large	  amounts	  of	  simple	  data	  
Aggregate-­‐Oriented	  Data	  hLp://marnfowler.com/bliki/AggregateOrientedDatabase.html	  “There is a significant downside...
BUT	  HOW	  TO	  EXPLOIT	  	  BIG	  DATA	  	  in	  the	  face	  of	  COMPLEXITY?	  
The	  	  big	  	  “Data	  Problem”	  
complexity = f(size, connectedness, variability)
hLp://en.wikipedia.org/wiki/File:Leonhard_Euler_2.jpg	  Meet	  Leonhard	  Euler	  •  Swiss	  mathemacian	  •  Inventor	  o...
Königsberg	  (Prussia)	  -­‐	  1736	  
A	  B	  D	  C	  
A	  B	  D	  C	  1"2"3"4"7"6"5"
hLp://www.bbc.co.uk/london/travel/downloads/tube_map.html	  
Property	  graphs	  •  Property	  graph	  model:	  – Nodes	  with	  properes	  – Named,	  directed	  relaonships	  with	  ...
Property	  Graph	  Model	  
Property	  graphs	  are	  very	  whiteboard-­‐friendly	  
Exploing	  data:	  	  Cypher	  query	  language	  •  Declarave	  graph	  paLern	  matching	  language	  – “SQL	  for	  gra...
Matching	  paLerns	  
Pathfinding	  
Logiscs	  
Entlements	  
Impact	  
BIG	  INSIGHTS	  FROM	  	  COMPLEX	  DATA	  
The	  	  “Big	  Data”	  problem	  The	  	  big	  	  “Data	  Problem”	  
Free	  O’Reilly	  eBook!	  Visit:	  hLp://GraphDatabases.com	  	  Ian Robinson,Jim Webber & Emil EifremGraphDatabaseshComp...
Thanks	  for	  listening	  Neo4j:	  hIp://neo4j.org	  Me:	  @rvanbruggen	  ,	  rik[at]neotechnology[dot]com	  
Neo4j - Rik Van Bruggen
Neo4j - Rik Van Bruggen
Neo4j - Rik Van Bruggen
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Neo4j - Rik Van Bruggen

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Slides from Rik Van Bruggen's talk on Exploiting Big Data with Graphs at the 18th Big Data London meetup.

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Neo4j - Rik Van Bruggen

  1. 1. Exploing  Big  Data  with  Graphs  Rik  Van  Bruggen  Regional  Director,  Neo  Technology  @rvanbruggen  
  2. 2. Roadmap  •  The  Relaonal  Crossroads  •  The  NOSQL  answer  – The  volume  answer  – The  complexity  answer  •  Exploing  Complexity  with  Graphs  •  Quesons  /  Answers  
  3. 3. The    “Big  Data”  problem  The    big    “Data  Problem”  
  4. 4. NOT  ONLY  SQL  
  5. 5. The    “Big  Data”  problem  
  6. 6. hLp://www.flickr.com/photos/crazyneighborlady/355232758/  
  7. 7. hLp://gallery.nen.gov.uk/image82582-­‐.html  
  8. 8. hLp://www.xtranormal.com/watch/6995033/mongo-­‐db-­‐is-­‐web-­‐scale  
  9. 9. Large  amounts  of  simple  data  
  10. 10. Aggregate-­‐Oriented  Data  hLp://marnfowler.com/bliki/AggregateOrientedDatabase.html  “There is a significant downside - the whole approach works really wellwhen data access is aligned with the aggregates, but what if you want tolook at the data in a different way? Order entry naturally stores orders asaggregates, but analyzing product sales cuts across the aggregate structure.The advantage of not using an aggregate structure in the database is that itallows you to slice and dice your data different ways for differentaudiences.This is why aggregate-oriented stores talk so much about map-reduce.”
  11. 11. BUT  HOW  TO  EXPLOIT    BIG  DATA    in  the  face  of  COMPLEXITY?  
  12. 12. The    big    “Data  Problem”  
  13. 13. complexity = f(size, connectedness, variability)
  14. 14. hLp://en.wikipedia.org/wiki/File:Leonhard_Euler_2.jpg  Meet  Leonhard  Euler  •  Swiss  mathemacian  •  Inventor  of  Graph  Theory  (1736)  
  15. 15. Königsberg  (Prussia)  -­‐  1736  
  16. 16. A  B  D  C  
  17. 17. A  B  D  C  1"2"3"4"7"6"5"
  18. 18. hLp://www.bbc.co.uk/london/travel/downloads/tube_map.html  
  19. 19. Property  graphs  •  Property  graph  model:  – Nodes  with  properes  – Named,  directed  relaonships  with  properes  – Relaonships  have  exactly  one  start  and  end  node  •  Which  may  be  the  same  node  
  20. 20. Property  Graph  Model  
  21. 21. Property  graphs  are  very  whiteboard-­‐friendly  
  22. 22. Exploing  data:    Cypher  query  language  •  Declarave  graph  paLern  matching  language  – “SQL  for  graphs”  – Columnar  results  •  Supports  graph  matching  commands  and  queries  – Find  me  stuff  like  this…  – Aggregaon,  ordering  and  limit,  etc.  
  23. 23. Matching  paLerns  
  24. 24. Pathfinding  
  25. 25. Logiscs  
  26. 26. Entlements  
  27. 27. Impact  
  28. 28. BIG  INSIGHTS  FROM    COMPLEX  DATA  
  29. 29. The    “Big  Data”  problem  The    big    “Data  Problem”  
  30. 30. Free  O’Reilly  eBook!  Visit:  hLp://GraphDatabases.com    Ian Robinson,Jim Webber & Emil EifremGraphDatabaseshComplimentsofNeoTechnology
  31. 31. Thanks  for  listening  Neo4j:  hIp://neo4j.org  Me:  @rvanbruggen  ,  rik[at]neotechnology[dot]com  
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