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  • 1. Data Access 2.0? …please welcome… Spring Data! Oliver Gierke
  • 2. Oliver GierkeSpring DataCore/JPA/MongoDBogierke@vmware.comwww.olivergierke.deolivergierke
  • 3. What to expect?
  • 4. How?Why? What?
  • 5. A Developer‘s View5
  • 6. What to expect? NOT!
  • 7. What to expect? NOT!7
  • 8. Retrospect
  • 9. Relational databases
  • 10. Scaling
  • 11. Data structures
  • 12. Hibari Voldemort Membase Riak Cassandra RedisSimpleDB (No)SQL MongoDB OrientDB CouchDB HBase Sones Neo4J
  • 13. Graphs
  • 14. Documents
  • 15. Column families
  • 16. Key Value
  • 17. Forest for the woods?
  • 18. A Developer‘s View18
  • 19. There‘s someSpring for that!
  • 20. Spring Data
  • 21. " … provide a familiar and consistent Spring-based programming model while not over-abstracting custom traits of the specific store.
  • 22. Spring Data JDBC JPA
  • 23. Spring Data JDBC JPA
  • 24. Spring Data JDBC JPA
  • 25. Spring Data JDBC JPA
  • 26. Spring Data JDBC JPA
  • 27. Building blocks
  • 28. Spring
  • 29. Mapping
  • 30. Templates
  • 31. Repositories
  • 32. Repositories Querydsl32
  • 33. DEMO
  • 34. Wrap up
  • 35. Wrap up• Sophisticated mapping support• Templates• Repositories• Querydsl• Spring namespace• Geospatial support• Cross-store persistence
  • 36. Questions?
  • 37. Resources• www.springframework.org/spring-data• github.com/SpringSource/spring-data-mongodb• http://www.se-radio.net/2010/07/episode-165-nosql-and- mongodb-with-dwight-merriman• http://kkovacs.eu/cassandra-vs-mongodb-vs-couchdb-vs- redis