Xebia Knowledge Exchange (may 2010) - NoSQL : Using the right tool for the right job

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The document discusses different types of databases and when each may be suitable. It covers relational databases like Oracle and SQL Server, then introduces NoSQL databases like Dynamo, MongoDB, Neo4j, Cassandra and HBase. It explains the needs that led to the creation of each type and provides brief descriptions of popular databases within each category.

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NoSQLUsing the right tool for the right job

www.xebia.fr / blog.xebia.fr 3 Not Only I / I / No SQL

www.xebia.fr / blog.xebia.fr 4 Not Only I / I / / / No SQL

www.xebia.fr / blog.xebia.fr 5 Not Only I / I / / / No SQL Relational

www.xebia.fr / blog.xebia.fr 6 Need to store some data ? Oracle SQL Server Sybase DB2 MySQL PostgreSQL

www.xebia.fr / blog.xebia.fr 7 RDBMS are great for relationalstorage !

www.xebia.fr / blog.xebia.fr 8 RDBMS may not befully trivial… …what a pity if youjustwanted a put / get store

www.xebia.fr / blog.xebia.fr 9 How to achieve scalability and highavailability with a RDMS ?

www.xebia.fr / blog.xebia.fr 10 Memcachedcan help to reduce the pressure on RDBMS

www.xebia.fr / blog.xebia.fr 11 But thiswasn’tenough for some people…

www.xebia.fr / blog.xebia.fr 12 The birth of Dynamo at Amazon.com… Temporal unavailability is acceptable Rich storage is preferred for reporting Write must ALWAYS be available Only key-value is required

www.xebia.fr / blog.xebia.fr 13 So theystarted to createtheirowndatabasethatwould match theirneeds…

www.xebia.fr / blog.xebia.fr 14 So theystarted to createtheirowndatabasethatwould match theirneeds…

www.xebia.fr / blog.xebia.fr 15 Consistent hashingspreadskeysuniformallyacross the partitions

www.xebia.fr / blog.xebia.fr 16 Shardingbringsscalability, replicationbringshighavailability

www.xebia.fr / blog.xebia.fr 17 But failuresstill have to behandledefficiently…

www.xebia.fr / blog.xebia.fr 18 In case of failure of a node, the 2 othernodes serve itsload

www.xebia.fr / blog.xebia.fr 19 In this configuration, clients know only few nodeswhichact as proxy to othernodes…

www.xebia.fr / blog.xebia.fr 20 Gossipprotocol to let everybody know node B has failed…

www.xebia.fr / blog.xebia.fr 21 Eventualconsistency… N = Number of replicas R = Number of readresponses to wait for W = Number of writeaknowledges to wait for

www.xebia.fr / blog.xebia.fr 22 The ratio between N, R and W makeseverything…

www.xebia.fr / blog.xebia.fr 23 The ratio between N, R and W makeseverything…

www.xebia.fr / blog.xebia.fr 24 The ratio between N, R and W makeseverything…

www.xebia.fr / blog.xebia.fr 26 Key-value stores are simple…

www.xebia.fr / blog.xebia.fr 27 Several competitors…

www.xebia.fr / blog.xebia.fr 30 Document orienteddatabases are an evolution of key-value stores

www.xebia.fr / blog.xebia.fr 31 MongoDBis the leader so far… … 10gen saidthey are the « MySQL of NoSQL »

www.xebia.fr / blog.xebia.fr 32 MongoDBis the leader so far…

www.xebia.fr / blog.xebia.fr 33 MongoDBis the leader so far…

www.xebia.fr / blog.xebia.fr 34 Graph databases are great to store… graphs !

www.xebia.fr / blog.xebia.fr 35 NeoTechnologyis the leader so far with Neo4j…

www.xebia.fr / blog.xebia.fr 37 Column-orienteddatabases have a veryparticular data model…

www.xebia.fr / blog.xebia.fr 38 Cassandra Vs HBase !

www.xebia.fr / blog.xebia.fr 39 Cassandra addsSuperColumns to this model…

www.xebia.fr / blog.xebia.fr 40 Cassandra wasdeveloppedatFacebook, to store the user messages

www.xebia.fr / blog.xebia.fr 41 Nowalsoused by Digg, Twitter, Rackspace,…

What a model… www.xebia.fr / blog.xebia.fr 42

www.xebia.fr / blog.xebia.fr 43 An example…

www.xebia.fr / blog.xebia.fr 44 Cassandra Demo

Cyrille Le Clerc (Xebia), Erwan Alliaume (Xebia), Jean Michel Bea (Fast Connect) ont présenté au Paris Java User Group les principes du Data Grid. Cache distribué, Network Attached Memory, Data Grid ou Cloud Computing sont des termes très à la mode qui s’inscrivent dans la même tendance. Nous présenterons pendant cette soirée le chemin qui nous à conduit d’un simple EH Cache à des grilles de centaines de giga octects de données qui s’étalent sur des data center. CACHES DISTRIBUES Les Cache Distribués se sont banalisés avec les frameworks Open Source Jboss Cache et EH Cache distribué. Où en sommes nous aujourd’hui ? - Quels sont les cas d’utilisation d’un cache distribué ? Quels gains en attendre ? - Comment migrer d’un cache local à un cache distribué ? Nos frameworks sont-ils adaptés à ces caches distribués ? - Comment fonctionne un cache distribué ? NETWORK ATTACHED MEMORY Le concept de Network Attached Memory a décollé dans l’univers Java avec Terracotta et offre à nos applications un espace mémoire encore inimaginable il y a peu. Que se cache-t-il derrière ? - Quels sont les cas d’utilisation des technologies de Network Attached Memory ? - Cette mémoire virtuellement infinie n’introduit-elle pas des contraintes ? - Si la mémoire est partagée, qu’en est-il des traitements ? - Quelles sont les perspectives des technologies de Network Attached Memory ? DATA GRID Le concept de data grid s’est popularisé avec les services Google Big Table ou Amazon S3 mais aussi avec des sites comme eBay qui annoncent des data center gigantesques. Cela va-t-il arriver dans l’informatique classique ? - Qu’est-ce qu’une grille de donnée ? Comment ça marche ? - Qui a besoin de Data Grid ? Est-ce réservé aux hyper scalable comme eBay ou Facebook ? Comment faisait-on avant ? En ai-je besoin ? - Comment structurer une application pour utiliser une grille de données ? Cela la change-t-il la façon de programmer ? - Map Reduce est-il un pattern utilisable avec une grille de données ? Est-ce le seul ? - Les grilles de données vont-elles remplacer les bases de données traditionnelles ? Comment peuvent-elles cohabiter ? DATA GRID, CLOUD ET LES AUTRES Data Grid, Grid Computing, Cloud Computing et eXtreme Transaction Processing (XTP) sont fréquement associés. Comment positionner Data Grid par rapport à ces technologies ? Quels positionnements ont les acteurs de cet univers ? Amazon S3&EC2 ? Coherence ? Gigaspace ? Google App engine & Big Table ? Grid Gain ? Terracotta ? Websphere eXtreme Scale ? Et les mainframes dans tout ça ?

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Xebia Knowledge Exchange (may 2010) - NoSQL : Using the right tool for the right job

1. NoSQLUsing the right tool for the right job

2. www.xebia.fr / blog.xebia.fr 2 No SQL

3. www.xebia.fr / blog.xebia.fr 3 Not Only I / I / No SQL

4. www.xebia.fr / blog.xebia.fr 4 Not Only I / I / / / No SQL

5. www.xebia.fr / blog.xebia.fr 5 Not Only I / I / / / No SQL Relational

6. www.xebia.fr / blog.xebia.fr 6 Need to store some data ? Oracle SQL Server Sybase DB2 MySQL PostgreSQL

7. www.xebia.fr / blog.xebia.fr 7 RDBMS are great for relationalstorage !

8. www.xebia.fr / blog.xebia.fr 8 RDBMS may not befully trivial… …what a pity if youjustwanted a put / get store

9. www.xebia.fr / blog.xebia.fr 9 How to achieve scalability and highavailability with a RDMS ?

10. www.xebia.fr / blog.xebia.fr 10 Memcachedcan help to reduce the pressure on RDBMS

11. www.xebia.fr / blog.xebia.fr 11 But thiswasn’tenough for some people…

12. www.xebia.fr / blog.xebia.fr 12 The birth of Dynamo at Amazon.com… Temporal unavailability is acceptable Rich storage is preferred for reporting Write must ALWAYS be available Only key-value is required

13. www.xebia.fr / blog.xebia.fr 13 So theystarted to createtheirowndatabasethatwould match theirneeds…

14. www.xebia.fr / blog.xebia.fr 14 So theystarted to createtheirowndatabasethatwould match theirneeds…

15. www.xebia.fr / blog.xebia.fr 15 Consistent hashingspreadskeysuniformallyacross the partitions

16. www.xebia.fr / blog.xebia.fr 16 Shardingbringsscalability, replicationbringshighavailability

17. www.xebia.fr / blog.xebia.fr 17 But failuresstill have to behandledefficiently…

18. www.xebia.fr / blog.xebia.fr 18 In case of failure of a node, the 2 othernodes serve itsload

19. www.xebia.fr / blog.xebia.fr 19 In this configuration, clients know only few nodeswhichact as proxy to othernodes…

20. www.xebia.fr / blog.xebia.fr 20 Gossipprotocol to let everybody know node B has failed…

21. www.xebia.fr / blog.xebia.fr 21 Eventualconsistency… N = Number of replicas R = Number of readresponses to wait for W = Number of writeaknowledges to wait for

22. www.xebia.fr / blog.xebia.fr 22 The ratio between N, R and W makeseverything…

23. www.xebia.fr / blog.xebia.fr 23 The ratio between N, R and W makeseverything…

24. www.xebia.fr / blog.xebia.fr 24 The ratio between N, R and W makeseverything…

25. www.xebia.fr / blog.xebia.fr 25

26. www.xebia.fr / blog.xebia.fr 26 Key-value stores are simple…

27. www.xebia.fr / blog.xebia.fr 27 Several competitors…

28. www.xebia.fr / blog.xebia.fr 28 Riak…

29. www.xebia.fr / blog.xebia.fr 29 Riak…

30. www.xebia.fr / blog.xebia.fr 30 Document orienteddatabases are an evolution of key-value stores

31. www.xebia.fr / blog.xebia.fr 31 MongoDBis the leader so far… … 10gen saidthey are the « MySQL of NoSQL »

32. www.xebia.fr / blog.xebia.fr 32 MongoDBis the leader so far…

33. www.xebia.fr / blog.xebia.fr 33 MongoDBis the leader so far…

34. www.xebia.fr / blog.xebia.fr 34 Graph databases are great to store… graphs !

35. www.xebia.fr / blog.xebia.fr 35 NeoTechnologyis the leader so far with Neo4j…

36. www.xebia.fr / blog.xebia.fr 36 Neo4j…

37. www.xebia.fr / blog.xebia.fr 37 Column-orienteddatabases have a veryparticular data model…

38. www.xebia.fr / blog.xebia.fr 38 Cassandra Vs HBase !

39. www.xebia.fr / blog.xebia.fr 39 Cassandra addsSuperColumns to this model…

40. www.xebia.fr / blog.xebia.fr 40 Cassandra wasdeveloppedatFacebook, to store the user messages

41. www.xebia.fr / blog.xebia.fr 41 Nowalsoused by Digg, Twitter, Rackspace,…

42. What a model… www.xebia.fr / blog.xebia.fr 42

43. www.xebia.fr / blog.xebia.fr 43 An example…

44. www.xebia.fr / blog.xebia.fr 44 Cassandra Demo

Xebia Knowledge Exchange (may 2010) - NoSQL : Using the right tool for the right job

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