soft-shake.ch - Data grids and Data Grids

745 views
686 views

Published on

Galder ZAMARREÑO

Published in: Technology
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
745
On SlideShare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
13
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

soft-shake.ch - Data grids and Data Grids

  1. 1. cocktail d’expérience informatiques Genève 3 & 4 octobre 2011 Seconde édition soft-shake.chAuteur Galder ZAMARREÑO Track JavaSession Data Grids vs Databases
  2. 2. Tuesday, October 11, 11
  3. 3. Tuesday, October 11, 11
  4. 4. Data Grids vs Databases Galder Zamarreño Senior Software Engineer Red Hat, Inc 3rd October 2011, Soft ShakeTuesday, October 11, 11
  5. 5. Galder Zamarreño • R&D Engineer, Red Hat Inc. • Infinispan developer • 5+ years exp. with distributed data systems • Twitter: @galderz • Blog: zamarreno.comTuesday, October 11, 11
  6. 6. Agenda • Why do we need Data Grids? • What are exactly In-memory Data Grids? • Data Grids + Databases • Data Grids without a Database • Can Data Grids replace Databases?Tuesday, October 11, 11
  7. 7. Traditionally... Store everything in a DB!Tuesday, October 11, 11
  8. 8. Modern requirements DBs not particularly good at horizontal scaling...Tuesday, October 11, 11
  9. 9. One size doesn’t fill all! DBs are not bad, but they’re not the solution to every problem eitherTuesday, October 11, 11
  10. 10. Data GridsTuesday, October 11, 11
  11. 11. Data Grids are not new Mainstream traction only recent: vertical scaling needs, cheaper memory... and cloud!Tuesday, October 11, 11
  12. 12. Who’s offering Data Grids?Tuesday, October 11, 11
  13. 13. The Players • Open Source: • Infinispan, EhCache, Hazelcast... • Commercial: • Oracle Coherence, Gigaspaces, Gemfire, IBM eXtreme ScaleTuesday, October 11, 11
  14. 14. But, what are In-memory DGs?Tuesday, October 11, 11
  15. 15. Definition In-memory data structures that offer extremely fast access to dataTuesday, October 11, 11
  16. 16. Maps are popular! Normally come with a Map-like API, but often come with alternativesTuesday, October 11, 11
  17. 17. Data distribution Store data in a subset of the grid to provide failover while being able to scale up!Tuesday, October 11, 11
  18. 18. With failure in mind Suitable for commodity hardware because they can handle failureTuesday, October 11, 11
  19. 19. Elastic Remain available during topology changesTuesday, October 11, 11
  20. 20. Durability More durability achieved flushing to a persistent storeTuesday, October 11, 11
  21. 21. Access patterns Embedded (client and DG in same VM) or Remote (just like DBs)Tuesday, October 11, 11
  22. 22. ACID or BASE Transactions or Eventual Consistency?Tuesday, October 11, 11
  23. 23. DGs + DBs?Tuesday, October 11, 11
  24. 24. Caching! Use Data Grids as caches to enhance Database access performance!Tuesday, October 11, 11
  25. 25. Can a Data Grid replace a DB?Tuesday, October 11, 11
  26. 26. Reiterating benefits Speed, scalability, cloud- friendliness...etcTuesday, October 11, 11
  27. 27. What are the Data Grid challenges?Tuesday, October 11, 11
  28. 28. Access patterns Migrating from SQL to Map or alternative APIs not easyTuesday, October 11, 11
  29. 29. Skill set Different skill set: OO programmer vs SQLTuesday, October 11, 11
  30. 30. Application data layer Data layer to take data collocation into account and do more validation (less strict schema)Tuesday, October 11, 11
  31. 31. E.g. with a DB...Tuesday, October 11, 11
  32. 32. Same with InfinispanTuesday, October 11, 11
  33. 33. Map/Reduce in detailTuesday, October 11, 11
  34. 34. Technology to bridge gap?Tuesday, October 11, 11
  35. 35. What about JPA? Hibernate OGM (Object/Grid Mapper) uses JPA to store in DGs as opposed to DBsTuesday, October 11, 11
  36. 36. Most frequent use cases for DGs?Tuesday, October 11, 11
  37. 37. Use cases • Analytic systems, i.e. financial/trading apps • XTP • Event driven apps, i.e. CEP • Clustering toolkitTuesday, October 11, 11
  38. 38. Do I see DGs as DB replacements?Tuesday, October 11, 11
  39. 39. DBs are here to stay! No. DBs are proven, mature, well understood plus, there are millions of systems out there!Tuesday, October 11, 11
  40. 40. One size doesn’t fill all! DBs are not a universal data storage system any moreTuesday, October 11, 11
  41. 41. Consider Data Grids For their speed, capabilities as data store, and cloud friendlinessTuesday, October 11, 11
  42. 42. Still some way to go More deployments and standardization (JSR-107, JSR-347)Tuesday, October 11, 11
  43. 43. Questions infinispan.org - @infinispan speakerrate.com/galderTuesday, October 11, 11

×