Voir aussi /informatique/SQL

MySQL

Microsoft SQL Server

http://www.postgresql.org

• SGBD : le mouvement anti-SQL s’amplifie ?

Google as inventé BigTable sur son Google File System (GFS) qui utilise le paradigme de MapReduce (Simplified Data Processing on Large Clusters) pour gérer d'énormes quantités de données dans une infrastructure distribuée.

D'autres qui ont des problématiques similaires lui ont emboité le pas comme Facebook avec Cassandra, …

Et heureusement, le monde de l'open source (Apache) n'est pas en retard car il y a Hbase sur Hadoop (HDFS).

Cassandra is a highly scalable, eventually consistent, distributed, structured key-value store. Cassandra brings together the distributed systems technologies from Dynamo and the data model from Google's BigTable. Like Dynamo, Cassandra is eventually consistent. Like BigTable, Cassandra provides a ColumnFamily-based data model richer than typical key/value systems.

Cassandra was open sourced by Facebook in 2008, where it was designed by one of the authors of Amazon's Dynamo. In a lot of ways you can think of Cassandra as Dynamo 2.0. Cassandra is in production use at Facebook but is still under heavy development.

Les plus gros acteurs du web (Facebook, Google, Amazon, Microsoft) ont été amenés à développer une base de données dédiées à la problématique du web car les bases de données relationnelles ne répondaient pas entièrement à leurs besoins. Facebook vient de livrer en opensource le code de son implémentation. Le nom du projet est Cassandra. Le langage utilisé pour développer est java.

• http://cassandra.apache.org
• http://www.25hoursaday.com/weblog/2008/07/14/ProjectCassandraFacebooksOpenSourceAlternativeToGoogleBigTable.aspx

• http://s3.amazonaws.com/AllThingsDistributed/sosp/amazon-dynamo-sosp2007.pdf
• http://en.wikipedia.org/wiki/Dynamo_(storage_system)

• http://labs.google.com/papers/bigtable.html
• http://labs.google.com/papers/bigtable-osdi06.pdf
• http://en.wikipedia.org/wiki/BigTable

http://hbase.apache.org

HBase is the Hadoop database. Use it when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables – billions of rows X millions of columns – atop clusters of commodity hardware. HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Hadoop. HBase includes:

• Convenient base classes for backing Hadoop MapReduce jobs with HBase tables including cascading, hive and pig source and sink modules
• Query predicate push down via server side scan and get filters
• Optimizations for real time queries
• A Thrift gateway and a REST-ful Web service that supports XML, Protobuf, and binary data encoding options
• Extensible jruby-based (JIRB) shell
• Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX

CouchDB est un projet de l'ASF (Apache Software Foundation).
Il s'agit d'une base de données avec une interface RestFul - JSON. Comme j'adore tout ce qui exploite pleinement HTTP, je me penche depuis quelques temps sur couchDB, notamment pour la participation à la création d'un frontEnd PHP pour Zend Framework : Zend_Couch (nom temporaire)

What CouchDB is:

• A document database server, accessible via a RESTful JSON API.
• Ad-hoc and schema-free with a flat address space.
• Distributed, featuring robust, incremental replication with bi-directional conflict detection and management.
• Query-able and index-able, featuring a table oriented reporting engine that uses Javascript as a query language.

What it is Not:

• A relational database.
• A replacement for relational databases.
• An object-oriented database. Or more specifically, meant to function as a seamless persistence layer for an OO programming language.

Voir:

• What CouchDB is sur le site du projet
• Article par Julien Pauli

Le clip I Use Couch DB de Couchio sur Vimeo :

http://www.mongodb.org

MongoDB is a very interesting document-oriented database implementation for several reasons:

• It uses JSON, instead of XML
• It is fast, as it is written in C++
• Supports index definitions
• Provides an easy to use query interface, very similar to some database abstraction layers
• Supports operations with sub-documents
• Provides a native PHP extension
• Supports auto-sharding
• Supports map-reduce for data transformation

Articles:

• Developing scalable PHP applications using MongoDB

  $collection = $db->selectCollection('people');
  // or  simply
  $collection = $db->people;