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MongoDB Logo.png
Developer(s) MongoDB Inc.
Initial release 2009 (2009)
Stable release 3.0.5 / 28 July 2015 (2015-07-28)
Development status Active
Written in C++, JavaScript, C
Operating system Cross-platform
Available in English
Type Document-oriented database
License GNU AGPL v3.0 (drivers: Apache license)

MongoDB (from humongous) is a cross-platform document-oriented database. Classified as a NoSQL database, MongoDB eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster. Released under a combination of the GNU Affero General Public License and the Apache License, MongoDB is free and open-source software.

First developed by the software company MongoDB Inc. in October 2007 as a component of a planned platform as a service product, the company shifted to an open source development model in 2009, with MongoDB offering commercial support and other services.[1] Since then, MongoDB has been adopted as backend software by a number of major websites and services, including Craigslist, eBay, Foursquare, SourceForge, Viacom, and The New York Times among others.[citation needed] As of 2014, MongoDB was the most popular NoSQL database system.[2]

Licensing and support[edit]

MongoDB is available for free under the GNU Affero General Public License.[3] The language drivers are available under an Apache License. In addition, MongoDB Inc. offers proprietary licenses for MongoDB.[1]

Main features[edit]

Some of the features include:[4]

Instead of taking a business subject and breaking it up into multiple relational structures, MongoDB can store the business subject in the minimal number of documents. For example, instead of storing title and author information in two distinct relational structures, title, author, and other title-related information can all be stored in a single document called Book.[5]
Ad hoc queries
MongoDB supports search by field, range queries, regular expression searches. Queries can return specific fields of documents and also include user-defined JavaScript functions.
Any field in a MongoDB document can be indexed (indices in MongoDB are conceptually similar to those in RDBMSes). Secondary indices are also available.
MongoDB provides high availability with replica sets.[6] A replica set consists of two or more copies of the data. Each replica set member may act in the role of primary or secondary replica at any time. The primary replica performs all writes and reads by default. Secondary replicas maintain a copy of the data of the primary using built-in replication. When a primary replica fails, the replica set automatically conducts an election process to determine which secondary should become the primary. Secondaries can also perform read operations, but the data is eventually consistent by default.
Load balancing
MongoDB scales horizontally using sharding.[7] The user chooses a shard key, which determines how the data in a collection will be distributed. The data is split into ranges (based on the shard key) and distributed across multiple shards. (A shard is a master with one or more slaves.)
MongoDB can run over multiple servers, balancing the load and/or duplicating data to keep the system up and running in case of hardware failure. Automatic configuration is easy to deploy, and new machines can be added to a running database.
File storage
MongoDB can be used as a file system, taking advantage of load balancing and data replication features over multiple machines for storing files.
This function, called GridFS,[8] is included with MongoDB drivers and available for development languages (see "Language Support" for a list of supported languages). MongoDB exposes functions for file manipulation and content to developers. GridFS is used, for example, in plugins for NGINX[9] and lighttpd.[10] Instead of storing a file in a single document, GridFS divides a file into parts, or chunks, and stores each of those chunks as a separate document.[11]
In a multi-machine MongoDB system, files can be distributed and copied multiple times between machines transparently, thus effectively creating a load-balanced and fault-tolerant system.
MapReduce can be used for batch processing of data and aggregation operations. The aggregation framework enables users to obtain the kind of results for which the SQL GROUP BY clause is used.
Server-side JavaScript execution
JavaScript can be used in queries, aggregation functions (such as MapReduce), and sent directly to the database to be executed.
Capped collections
MongoDB supports fixed-size collections called capped collections. This type of collection maintains insertion order and, once the specified size has been reached, behaves like a circular queue.


In some failure scenarios where an application can access two distinct MongoDB processes, but these processes cannot access each other, it is possible for MongoDB to return stale reads. In this scenario it is also possible for MongoDB to acknowledge writes that will be rolled back.[12]

Before version 2.2, concurrency control was implemented on a per-mongod basis. With version 2.2, concurrency control was implemented at the database level.[13] Since version 3.0,[14] pluggable storage engines were introduced, and each storage engine may implement concurrency control differently.[15] With MongoDB 3.0 concurrency control is implemented at the collection level for the MMAPv1 storage engine,[16] and at the document level with the WiredTiger storage engine.[17] With versions prior to 3.0, one approach to increase concurrency is to use sharding.[18] In some situations, reads and writes will yield their locks. If MongoDB predicts a page is unlikely to be in memory, operations will yield their lock while the pages load. The use of lock yielding expanded greatly in 2.2.[19]

Another criticism is related to the limitations of MongoDB when used on 32-bit systems.[20] In some cases, this was due to inherent memory limitations.[21] MongoDB recommends 64-bit systems and that users provide sufficient RAM for their working set. Some users experience increased latency when their working set exceeds available RAM and the system encounters page faults. Compose, a provider of managed MongoDB infrastructure, recommends a scaling checklist for large systems.[22]

Additionally, MongoDB does not support collation-based sorting and is limited to byte-wise comparison via memcmp,[23] which will not provide correct ordering for many non-English languages[24] when used with a Unicode encoding.

Language support[edit]

MongoDB has official drivers for a variety of popular programming languages and development environments.[25] There are also a large number of unofficial or community-supported drivers for other programming languages and frameworks.[26]

Management and graphical front-ends[edit]

Third-Party GUI tools[edit]

Record insertion in MongoDB with Robomongo 0.8.5.

There is an active and growing community of developers building third-party rich GUI tools for the MongoDB. Some relevant examples (listed in alphabetical order):

  • 3T MongoChef, cross-platform MongoDB GUI
  • BI Studio, Business Intelligence frontend for MongoDB.
  • Database Master, web-based client software, supports RDMS
  • Fang of Mongo, web-based UI, built with Django and jQuery
  • FusionReactor, Java based Application Monitor for MongoDB
  • Futon4Mongo, a clone of the CouchDB-Futon-Web-Interface for MongoDB
  •, Web based GUI for MongoDB
  • mms, Mongo Management Studio, cross-platfrorm and web-based GUI
  • Mongo3, ruby-based GUI
  • MongoHub, a native OS-X-application for MongoDB management
  • NoSQL Manager for MongoDB, a MS Windows GUI application for MongoDB management with Shell
  • Opricot, browser-based MongoDB-Shell, implemented in PHP
  • Robomongo, Shell-centric cross-platform MongoDB management tool
  • SlamData, enables running SQL queries on a MongoDB database
  • UMongo (JMongoBrowser), cross-platform Management-GUI, implemented in Java


As of July 2015, MongoDB is the fourth most popular type of database management system, and the most popular for document stores.[2]

Production deployments[edit]

Large-scale deployments of MongoDB are tracked by MongoDB Inc. Notable users of MongoDB include:

See also[edit]


  1. ^ a b "10gen embraces what it created, becomes MongoDB Inc.". Gigaom. Retrieved 27 August 2013. 
  2. ^ a b "Popularity ranking of database management systems". Solid IT. Retrieved 2015-07-04. 
  3. ^ The MongoDB NoSQL Database Blog, The AGPL
  4. ^ MongoDB Developer Manual
  5. ^ Data Modeling for MongoDB
  6. ^ Introduction to Replication
  7. ^ Introduction to Sharding
  8. ^ GridFS article on MongoDB Developer's Manual
  9. ^ NGINX plugin for MongoDB source code
  10. ^ lighttpd plugin for MongoDB source code
  11. ^ Expertstown - MongoDB overview
  12. ^ Kyle Kingsbury (2015-04-20). "Call me maybe: MongoDB stale reads". Retrieved 2015-07-04. 
  13. ^ MongoDB Jira Ticket 4328
  14. ^ Eliot Horowitz (2015-01-22). "Renaming Our Upcoming Release to MongoDB 3.0". Retrieved 2015-02-23. 
  15. ^ [1] - MongoDB 2.8 release
  16. ^ MMAPv1 Concurrency Improvement
  17. ^ WiredTiger Concurrency and Compression
  18. ^ FAQ Concurrency - How Does Sharding Affect Concurrency
  19. ^ FAQ Concurrency - Do Operations Ever Yield the Lock
  20. ^ 32-bit Limitations
  21. ^ Does Everybody Hate MongoDB
  22. ^ [2]
  23. ^ "memcmp". 31 May 2013. Retrieved 26 April 2014. 
  24. ^ MongoDB Jira ticket 1920
  25. ^ "MongoDB Drivers and Client Libraries". Retrieved 2013-07-08. 
  26. ^ "Community Supported Drivers". Retrieved 2014-07-09. 
  27. ^ Presentation by Amadeus 11/2014
  28. ^ Holy Large Hadron Collider, Batman!
  29. ^ MongoDB at eBay
  30. ^ Experiences Deploying MongoDB on AWS
  31. ^ Presentation by LinkedIn
  32. ^ "Metlife uses nosql for customer service". Information Week. Retrieved 8 November 2014. 
  33. ^ The Quest to Understand the Use of MongoDB in the SAP PaaS
  34. ^ Real World NoSQL: MongoDB at Shutterfly
  35. ^ Here's How We Think Of Shutterfly's Stock Value
  36. ^ Scaling SourceForge with MongoDB


External links[edit]