NoSQL
Non-relational data stores Eric Evans, Rackspace, early 2009
Not only SQL No to SQL
 
Giving up ACID Eventual consistency Schemaless Scale horizontally
ACID Atomicity Consistency Isolation Durability
BASE Basically Available Soft state Eventually consistent
1. Key Value stores
Redis C in memory journal append-only file list/set/sorted set boolean operation
Erlang similar to Redis in memory EU sponsored Scalaris
Mixi (Facebook japonais) Tokyo Tyrant (client) Tokyo Cabinet (server) several server mecanism asynchronous replication mul...
Java LinkedIn in memory pluggable storage Project Voldemort
Erlang REST JSON in memory or disk Riak
2. Document stores
Amazon Web Services proprietary pay as you go SimpleDB
Erlang Apache map/reduce in Javascript REST JSON CouchDB
C++ 10gen query & map/reduce in Javascript socket BSON (Binary JSON) automatic sharding GridFS master/slave asynchronous r...
3. Extensible record stores
” Bigtable: A Distributed Storage System for Structured Data”
Java Apache BigTable w Hadoop (DFS) HBase
C++ Zvents, Baidu very similar to Hbase needs DFS (like Hadoop) HQL HyperTable
Java Facebook then Apache very similar to Hbase marriage of Dynamo and BigTable supercolumn, column tunable concistency de...
For who ?
” If you're asking me, should I use a NoSQL store ? Then the answer is no.”
!CouchDB MongoDB Redis (?) Our choice @novelys
pretty straightforward pretty close from our previous DB drivers developped in parallel several ODM in Ruby schema-less ! ...
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NoSQL

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Introductiion à NoSQL dans le cadre des Last Thursday strasbourgeois http://www.facebook.com/home.php#!/group.php?gid=44635341639&ref=ts

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NoSQL

  1. 1. NoSQL
  2. 2. Non-relational data stores Eric Evans, Rackspace, early 2009
  3. 3. Not only SQL No to SQL
  4. 5. Giving up ACID Eventual consistency Schemaless Scale horizontally
  5. 6. ACID Atomicity Consistency Isolation Durability
  6. 7. BASE Basically Available Soft state Eventually consistent
  7. 8. 1. Key Value stores
  8. 9. Redis C in memory journal append-only file list/set/sorted set boolean operation
  9. 10. Erlang similar to Redis in memory EU sponsored Scalaris
  10. 11. Mixi (Facebook japonais) Tokyo Tyrant (client) Tokyo Cabinet (server) several server mecanism asynchronous replication multi-master, master/slave map/reduce in Lua API compatibility w Memcached in memory or disk Tokyo Tyrant
  11. 12. Java LinkedIn in memory pluggable storage Project Voldemort
  12. 13. Erlang REST JSON in memory or disk Riak
  13. 14. 2. Document stores
  14. 15. Amazon Web Services proprietary pay as you go SimpleDB
  15. 16. Erlang Apache map/reduce in Javascript REST JSON CouchDB
  16. 17. C++ 10gen query & map/reduce in Javascript socket BSON (Binary JSON) automatic sharding GridFS master/slave asynchronous replication MongoDB
  17. 18. 3. Extensible record stores
  18. 19. ” Bigtable: A Distributed Storage System for Structured Data”
  19. 20. Java Apache BigTable w Hadoop (DFS) HBase
  20. 21. C++ Zvents, Baidu very similar to Hbase needs DFS (like Hadoop) HQL HyperTable
  21. 22. Java Facebook then Apache very similar to Hbase marriage of Dynamo and BigTable supercolumn, column tunable concistency decentralized fault tolerant (data center) elasticity Cassandra
  22. 23. For who ?
  23. 24. ” If you're asking me, should I use a NoSQL store ? Then the answer is no.”
  24. 25. !CouchDB MongoDB Redis (?) Our choice @novelys
  25. 26. pretty straightforward pretty close from our previous DB drivers developped in parallel several ODM in Ruby schema-less ! easy querying no fulltext search (well not really) rethinking how we store data kind of builtin denormalization Experience w Mongo http://www.rocketblogging.com

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