Downloaded 31 times
![NoSQL Mobile Databases
[Lite]](https://image.slidesharecdn.com/nosqlday2013-131120052142-phpapp02/85/NoSQL-Containers-get-Rich-34-320.jpg)
![FILTERED
ShardingMULTI-MASTER REPLICATION
Shard 1
[A to F]
Shard 2
[G to N]
Shard 3
[O to T]
Shard 4
[U to Z]](https://image.slidesharecdn.com/nosqlday2013-131120052142-phpapp02/85/NoSQL-Containers-get-Rich-60-320.jpg)
![FILTERED MULTI-MASTER REPLICATION
Scaling writes
client
Shard 1
[A to F]
Shard 2
[G to N]
Shard 3
[O to T]
Shard 4
[U to Z]](https://image.slidesharecdn.com/nosqlday2013-131120052142-phpapp02/85/NoSQL-Containers-get-Rich-61-320.jpg)
![FILTERED MULTI-MASTER REPLICATION
Scaling writes
client
Shard 1
[A to F]
Shard 2
[G to N]
Shard 3
[O to T]
Shard 4
[U to Z]](https://image.slidesharecdn.com/nosqlday2013-131120052142-phpapp02/85/NoSQL-Containers-get-Rich-62-320.jpg)
![Schemaless
$doc = $myDb->getDoc('the_godfather');
$year = $doc['year'];
$castCount = count($doc['cast']);
if ($castCount > 0) {
$firstCastName = $doc['cast'][0]['name'];
}](https://image.slidesharecdn.com/nosqlday2013-131120052142-phpapp02/85/NoSQL-Containers-get-Rich-89-320.jpg)
![Schemaless
…are you sure?
$doc = $myDb->getDoc('the_godfather');
$year = $doc['year'];
$castCount = count($doc['cast']);
if ($castCount > 0) {
$firstCastName = $doc['cast'][0]['name'];
}
The application is aware of
document schema!](https://image.slidesharecdn.com/nosqlday2013-131120052142-phpapp02/85/NoSQL-Containers-get-Rich-90-320.jpg)
Uploaded byStefano Valle
NoSQL Containers get Rich
The document discusses various NoSQL data models including key-value, document, column-family, and graph databases and their applications in big data scenarios. It emphasizes the importance of scalability, durability, performance, and the CAP theorem in selecting a suitable NoSQL solution. It also highlights the significance of understanding data lifecycle and application design when employing NoSQL databases.
NoSQL Containers get Rich
- 1. Containers get Rich NoSQLDay, Udine – Italy 15-11-2013
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- 4. THE BIG DATAWE USE EVERY DAY
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- 6. OMG! How tochoose?
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- 9. nosqlday http://nosqlday.it // Store value >SET nosqlday http://nosqlday.it // Retrieve value > GET nosqlday http://nosqlday.it
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- 15. Year Cast Rating 1994 Tom Hanks, Robin Wright, GarySinise 8,7 Braveheart 1995 Mel Gibson, Sophie Marceau, Patrick McGoohan Fast & Furious 7 2014 Forrest Gump
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- 21. Classification by datamodel Key - value Column 21 Document Graph
- 22. Is all about datamodel?
- 23. Let’s suppose existsa RDBMS «category»… 23
- 24. Let’s suppose existsa RDBMS «category»… 24
- 25. NOSQL ARE SIMPLY DATACONTAINERS?
- 26. Many more to sayabout NoSQL datastores
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- 36. ALL useful things! butdon’t limit to features-first comparison
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- 38. Durability vs Performance _______ _______ _______ _______ _______ 38 safemode? off = data loss risk
- 39. Durability vs Performance safemode? off = data loss risk _______ _______ _______ _______ _______ file system 39
- 40. Durability vs Performance safemode? off = data loss risk _______ _______ _______ _______ _______ Consider use of Journaling file system 40
- 41. Durability vs Performance safemode? off = data loss risk _______ _______ _______ _______ _______ Disk / RAID cache? file system 41
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- 44. Goldfish, not thoroughbreds Scaleout Scale up
- 45. Goldfish, not thoroughbreds Allowfor fast, cost-effective, on-demand growth (or shrink) Scale out Scale up
- 46. "I know twocompanies that collapsed due to inability to reduce operating costs when the utilization of their sites diminished" Theo Schlossnagle From Theo’s book "Scalable Internet Architectures"
- 47. Ease of scalability KeyValue stores ColumnFamily stores Document databases Graph databases > 90%of use cases Complexity Adapted from http://www.slideshare.net/emileifrem/an-overview-of-nosql-jfokus-2011
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- 49. Query capability function(doc) { if(doc.city == ‘London’) { emit(doc._id, null) } } 49
- 50. Query capability We couldn’tuse user input here function(doc) { if (doc.city == ???) { emit(doc._id, null) } } 50
- 51. Query capability db.events.find( { city:‘Rome’ } ) Here we could use user input! function(doc) { if (doc.city == ???) { emit(doc._id, null) } } 51
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- 53. FILTERED MULTI-MASTER S Distribution model: MREPLICATION MASTER all data SLAVE
- 54. FILTERED MULTI-MASTER M Distribution model: MREPLICATION MASTER MASTER MASTER
- 55. FILTERED MULTI-MASTER Filtered multi-masterREPLICATION Product list MASTER MASTER (eg. head quarter) (eg. customer plant) Purchases
- 56. FILTERED MULTI-MASTER REPLICATION Scalingreads MASTER MASTER MASTER
- 57. FILTERED MULTI-MASTER REPLICATION Scalingreads client client MASTER MASTER MASTER client
- 58. FILTERED MULTI-MASTER REPLICATION Scalingwrites? MASTER MASTER MASTER
- 59. FILTERED MULTI-MASTER REPLICATION Scalingwrites? client MASTER MASTER MASTER
- 60. FILTERED ShardingMULTI-MASTER REPLICATION Shard 1 [Ato F] Shard 2 [G to N] Shard 3 [O to T] Shard 4 [U to Z]
- 61. FILTERED MULTI-MASTER REPLICATION Scalingwrites client Shard 1 [A to F] Shard 2 [G to N] Shard 3 [O to T] Shard 4 [U to Z]
- 62. FILTERED MULTI-MASTER REPLICATION Scalingwrites client Shard 1 [A to F] Shard 2 [G to N] Shard 3 [O to T] Shard 4 [U to Z]
- 63. R / Wdata from 2 nodes 63
- 64. R / Wdata from 2 nodes T1 Node 1 C X=0 Node 2 C X=0 64
- 65. R / Wdata from 2 nodes T1 T2 Node 1 C X=0 C X=1 Node 2 C X=0 C X=0 65
- 66. R / Wdata from 2 nodes T1 T2 Node 1 C X=0 C X=1 Node 2 C X=0 C X=0 66
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- 69. (Some of) availablesolutions CP: BigTable Hbase MongoDB Redis MemcacheDB etc. PA: Dynamo CouchDB Cassandra SimpleDB Tokyo Cabinet Voldemort etc. 69 CA: RDBMS etc. Consistency Partition Tolerance Availability
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- 74. Aggregates Source: AggregateOrientedDatabase -http://martinfowler.com/bliki/AggregateOrientedDatabase.html 74
- 75. Aggregates Atomicity and Isolation areguaranteed inside an aggregate Source: AggregateOrientedDatabase - http://martinfowler.com/bliki/AggregateOrientedDatabase.html 75
- 76. ARE YOU SUREWE NEED ACID?
- 77. ARE YOU SUREWE NEED ACID?
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- 81. Data Model STARTING FROMDATA MODEL…
- 82. Scalability model Data durability Query model Position onCAP Some needful feature Performance Data Model MANY OTHER THINGS TO CONSIDER
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- 85. "the relational model ispretty magical" Laurie Voss http://seldo.com/weblog/2010/07/12/in_defence_of_sql
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- 87. "Big data islike teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it..." Dan Ariely https://www.facebook.com/dan.ariely/posts/904383595868
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- 89. Schemaless $doc = $myDb->getDoc('the_godfather'); $year= $doc['year']; $castCount = count($doc['cast']); if ($castCount > 0) { $firstCastName = $doc['cast'][0]['name']; }
- 90. Schemaless …are you sure? $doc= $myDb->getDoc('the_godfather'); $year = $doc['year']; $castCount = count($doc['cast']); if ($castCount > 0) { $firstCastName = $doc['cast'][0]['name']; } The application is aware of document schema!
- 91. Polyglot persistence Farm Node 1 Provisioning LAPPstack Node n 91 Devices status Data aggregation
- 92. Polyglot persistence madesafe Other component Provisioning layer 92
- 93. Polyglot persistence madesafe Other component Data Store as a Service Provisioning layer 93
- 94. Polyglot persistence madesafe Other component Provisioning Anti Corruption Layer 94 layer
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- 96. GOOD APPLICATION DESIGN THINKABOUT DATA LIFECYCLE
- 97. GOOD APPLICATION DESIGN THINKABOUT DATA LIFECYCLE NOT ONLY DATA MODEL
- 98. That’s all, folks! StefanoValle @stefanovalle s.valle@mvassociati.it
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