History of MongoDB

Last update Jun. 3^rd 2015 10:30:00 PM

Creation date Apr. 26^th 2011 8:34:37 PM

• 
  Alexis on Jun. 3^rd 2015 10:30:00 PMReport

  Release date

  2015-05-12

  Latest version

  3.0.3

• 
  Romans Malinovskis on Jun. 3^rd 2015 12:07:29 PMReport

  Embedded Language

  JavaScript

  Domain-model Aggregation

  yes

  GeoSpatial

  yes

  Consistency

  Eventual (strong with flag)

  Data Presentation

  JSON

  Pricing

  Free download or Pay per instance + Service (MongoLab)

  Commercial Support

  Third parties.

  Cloud DB

  Third Party

• 
  Alexis on May 9^th 2011 9:40:30 PMReport

  Initial release

  2009

• 
  Alexis on May 9^th 2011 9:33:58 PMReport

  Latest version

  1.8.1

  Release date

  2011-04-06

• 
  Alexis on May 9^th 2011 9:14:38 PMReport

  Projects using it

  • bit.ly
  • diaspora
  • Shutterfly
  • foursquare
  • SourceForge

• 
  Alexis on May 9^th 2011 9:13:37 PMReport

  Projects using it

  • diaspora
  • Shutterfly
  • foursquare

• 
  Alexis on May 9^th 2011 8:49:28 PMReport

  Viewer

  public

• 
  Alexis on May 9^th 2011 8:25:36 PMReport

  Replication

  Master/slave

  Platforms

  Cross-platform

• 
  Alexis on May 9^th 2011 8:15:32 PMReport

  Replication

  master/slave

• 
  Alexis on May 9^th 2011 8:10:34 PMReport

  Transaction support

  no

• 
  Alexis on May 9^th 2011 8:03:56 PMReport

  Best used

  If you need dynamic queries. If you prefer to define indexes, not map/reduce functions. If you need good performance on a big DB. If you wanted CouchDB, but your data changes too much, filling up disks.

• 
  Alexis on Apr. 26^th 2011 8:37:25 PMReport

  Wikipedia

  http://en.wikipedia.org/wiki/MongoDB

• 
  Alexis on Apr. 26^th 2011 8:34:37 PMReport

  Mode

  70

  Name

  MongoDB

  Viewer

  unlisted

  Editor

  alexis

  Category

  it-development

  Website

  http://www.mongodb.org/

  Development language

  C++

  License

  AGPL (Drivers: Apache)

  Protocol

  BSON (Binary)

  Best used

  If you need dynamic queries. If you prefer to define indexes, not map/reduce functions. If you need good performance on a big DB. If you wanted CouchDB, but your data changes too much, filling up disks.

  Usage example

  For all things that you would do with MySQL or PostgreSQL, but having predefined columns really holds you back.

  Main focus

  Retains some friendly properties of SQL. (Query, index)