Data in your SOA: From SQL to NoSQL and Beyond
0 likes1,125 views
The document discusses different data storage options for enterprises, including relational databases, NoSQL databases, file systems, caches, and message queues. It explores attributes like data type, volume, access patterns, and lifecycle that should be considered when selecting a storage solution. Relational databases are best for transactional workloads with structured data and queries, while NoSQL column-family databases can scale for unstructured data and high volumes. A hybrid approach may be needed for complex workloads. The WSO2 platform supports both relational and NoSQL options through integrated services.
![pass
thru
msg
middleware
app
con]igurations
meta
data
39](https://image.slidesharecdn.com/data-in-your-soa-111216001640-phpapp02/85/Data-in-your-SOA-From-SQL-to-NoSQL-and-Beyond-39-320.jpg)
![large
]iles
]ile
system
transactional
support
57](https://image.slidesharecdn.com/data-in-your-soa-111216001640-phpapp02/85/Data-in-your-SOA-From-SQL-to-NoSQL-and-Beyond-57-320.jpg)
![[[example]]
81](https://image.slidesharecdn.com/data-in-your-soa-111216001640-phpapp02/85/Data-in-your-SOA-From-SQL-to-NoSQL-and-Beyond-81-320.jpg)
![[[example]]
83](https://image.slidesharecdn.com/data-in-your-soa-111216001640-phpapp02/85/Data-in-your-SOA-From-SQL-to-NoSQL-and-Beyond-83-320.jpg)
Data in your SOA: From SQL to NoSQL and Beyond
- 1. 1
- 2. In WSO2Con 2010…. 2
- 3. 3
- 4. topic: Unleash the power of enterprise data 4
- 5. power of data 5
- 6. data centricity 6
- 7. 7
- 8. why 8
- 9. how 9
- 10. 10
- 11. this year … 11
- 12. topic : Data in your SOA -‐ SQL to NoSQL 12
- 13. storage options 13
- 14. selection 14
- 15. “Data in your SOA ” : SQL to NoSQL 15
- 16. data 16
- 17. located in 17
- 18. 18
- 19. has 19
- 20. attributes 20
- 21. <attributes> 21
- 22. #1. lifecycle 22
- 23. #2. owner (provenance) 23
- 24. #3. access pattern 24
- 25. #4. structure 25
- 26. #5. no-‐structure 26
- 27. #6. semi-‐structure 27
- 28. </attributes> 28
- 29. some examples.. 29
- 30. CNN iReport 30
- 31. News items Multi media CNN iReport linked access patterns tagged searched 31
- 32. Facebook 32
- 33. images user accounts Facebook relationships discussions 33
- 34. Point of Sales App 34
- 35. item list Point of Sales App mode of payment 35
- 36. Amazon.com 36
- 37. Suppliers Products Orders Amazon.com History relationships 37
- 38. middleware app 38
- 39. pass thru msg middleware app con]igurations meta data 39
- 40. how data are stored? 40
- 41. or, how would you be doing it? 41
- 42. <expectations> 42
- 43. reliable storage 43
- 44. retrieval 44
- 45. update 45
- 47. </expectations> 47
- 48. options 48
- 49. 49
- 50. <options> 50
- 51. transactional de facto standard relational databases read/write/search moderate scaling 51
- 52. built-‐in functionality spreadsheets familiarity single user 52
- 53. API online spreadsheets multi user 53
- 54. Google Fusion Tables 54
- 55. synchronize processing speed message queues reliable transactional temporarily storage 55
- 56. specialized APIs registries manageability 56
- 57. large ]iles ]ile system transactional support 57
- 58. fast no persistence cache(local/distributed) no search key memory 58
- 59. NoSQL column family 59
- 60. why? 60
- 61. Internet 61
- 62. applications 62
- 63. scaling 63
- 64. users 64
- 65. Big Data 65
- 66. nosql-‐database.org (122+) 66
- 67. document databases 67
- 68. key/value storages 68
- 69. object databases 69
- 70. XML databases 70
- 71. many more... 71
- 72. </options> 72
- 73. different data models 73
- 74. how to select? 74
- 75. things to consider… 75
- 76. questions to ask… 76
- 77. <questions> 77
- 78. data type 78
- 79. <types> 79
- 80. structured 80
- 81. [[example]] 81
- 82. un-‐structured 82
- 83. [[example]] 83
- 84. semi-‐structured 84
- 85. <types> 85
- 86. volume & growth 86
- 87. scalability 87
- 88. #1: vertical 88
- 89. #2: horizontal 89
- 90. <horizontal> 90
- 91. eg: MySQL mirroring/ clustering 91
- 92. limitations 92
- 93. CAP theorem consistency availability Partition tolerance 93
- 94. </horizontal> 94
- 95. data access patterns 95
- 96. <patterns> 96
- 97. archival 97
- 98. Analytics (OLAP) 98
- 99. OLTP 99
- 100. </patterns> 100
- 101. <retrieval> 101
- 102. #1: sequential 102
- 103. #2: key based 103
- 104. supports : un-‐structured, structured 104
- 105. #3: query based 105
- 106. supports : structured 106
- 107. </retrieval> 107
- 108. life span 108
- 109. transaction support 109
- 110. manageability 110
- 111. </questions> 111
- 112. <some guidelines> 112
- 113. transaction intensive 113
- 114. small scale, 114
- 115. JOINs 115
- 116. relational databases. 116
- 117. un-‐structured data, 117
- 118. no search 118
- 119. key/value storages 119
- 120. or column family. 120
- 121. potential for SCALING 121
- 122. writes && reads 122
- 123. relational databases 123
- 124. not the best choice. 124
- 125. hybrid 125
- 126. approaches. 126
- 127. build 127
- 128. expertise. 128
- 129. your data 129
- 130. data model 130
- 131. storage engine. 131
- 132. Don’t 132
- 133. COP/ROP. 133
- 134. </some guidelines> 134
- 135. WSO2 platform 135
- 136. on premise 136
- 137. or Java PaaS 137
- 138. applications 138
- 139. need 139
- 140. data storage 140
- 141. can make use of 141
- 142. WSO2 Message Broker (MB) 142
- 143. WSO2 Relational Storage Service (RSS) 143
- 144. WSO2 Cassandra Storage Service (CSS) 144
- 145. WSO2 Governance Registry 145
- 146. WSO2 CSG 146
- 147. more on line up 147
- 148. interested? 148
- 149. tutorial session 149
- 150. problems !! 150
- 151. heterogeneous storages 151
- 152. in summary… 152
- 153. no silver bullet 153
- 154. analyze, choose right one 154
- 155. thank you. 155