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Developer(s) MongoDB Inc.
Initial release 2009 (2009)
Stable release 2.6.5 / 7 October 2014 (2014-10-07)
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)
Website .org.mongodbwww

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 10gen (now Viacom, and the New York Times, among others. MongoDB is the most popular NoSQL database system.[2]


  • Licensing and support 1
  • Main features 2
  • Criticisms 3
  • Language support 4
  • Management and graphical front-ends 5
    • Official MongoDB tools 5.1
    • Third-Party GUI tools 5.2
  • Popularity 6
  • Production deployments 7
  • See also 8
  • References 9
  • Bibliography 10
  • External links 11

Licensing and support

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 commercial licenses for MongoDB.[1]

Main features

Some of the main 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, which is much more intuitive and usually easier to work with.[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 on 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 with no difficulty 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.


Prior to November 2012, MongoDB's default consistency model ("write concern") acknowledged writes as soon as they had entered the client's outgoing queue,[12] meaning that the default setup was vulnerable to client crashes.

MongoDB uses a readers-writer lock that allows concurrent read access to a database but exclusive write access to a single write operation. Before version 2.2, this lock was implemented on a per-mongod basis. Since version 2.2, the lock has been implemented at the database level.[13] One approach to increase concurrency is to use sharding.[14] 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.[15]

Another criticism is related to the limitations of MongoDB when used on 32-bit systems.[16] In some cases, this was due to inherent memory limitations.[17] MongoDB recommends 64-bit systems and that users provide sufficient RAM for their working set. Some users encounter issues when their working set exceeds available RAM and the system encounters page faults. MongoHQ, a provider of managed MongoDB infrastructure, recommends a scaling checklist for large systems.[18]

Additionally, MongoDB does not support collation-based sorting and is limited to byte-wise comparison via memcmp,[19] which will not provide correct ordering for many non-English languages[20] when used with a Unicode encoding.

Language support

MongoDB has official drivers for a variety of popular programming languages and development environments.[21] There are also a large number of unofficial or community-supported drivers for other programming languages and frameworks.[22]

Management and graphical front-ends

Official MongoDB tools

In a MongoDB installation the following commands are available:

MongoDB offers an interactive shell called mongo,[23] which lets developers view, insert, remove, and update data in their databases, as well as get replication information, set up sharding, shut down servers, execute JavaScript, and more.
Administrative information can also be accessed through a web interface,[24] a simple webpage that serves information about the current server status. By default, this interface is 1000 ports above the database port (28017).
mongostat[25] is a command-line tool that displays a summary list of status statistics for a currently running MongoDB instance: how many inserts, updates, removes, queries, and commands were performed, as well as what percentage of the time the database was locked and how much memory it is using. This tool is similar to the UNIX/Linux vmstat utility.
mongotop[26] is a command-line tool providing a method to track the amount of time a MongoDB instance spends reading and writing data. mongotop provides statistics on the per-collection level. By default, mongotop returns values every second. This tool is similar to the UNIX/Linux Top (Unix) utility.
mongosniff[27] is a command-line tool providing a low-level tracing/sniffing view into database activity by monitoring (or "sniffing") network traffic going to and from MongoDB. mongosniff requires the Libpcap network library and is only available for Unix-like systems. A cross-platform alternative is the open source Wireshark packet analyzer which has full support for the MongoDB wire protocol.
mongoimport, mongoexport
mongoimport[28] is a command-line utility to import content from a JSON, CSV, or TSV export created by mongoexport[29] or potentially other third-party data exports.
mongodump, mongorestore
mongodump[30] is a command-line utility for creating a binary export of the contents of a Mongo database; mongorestore[31] can be used to reload a database dump.

Third-Party GUI tools

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,[32] cross-platform MongoDB GUI
  • BI Studio, Business Intelligence frontend for MongoDB.
  • Database Master, web-based client software, supports RDMS
  • Fang of Mongo,[33] web-based UI, built with Django and jQuery
  • Futon4Mongo,[34] a clone of the CouchDB-Futon-Web-Intterface for MongoDB
  • mms, Mongo Management Studio,[35] cross-platfrorm and web-based GUI
  • Mongo3,[36] ruby-based GUI
  • MongoHub,[37] a native OS-X-application for MongoDB management
  • Opricot',[38] browser-based MongoDB-Shell, implemented in PHP
  • UMongo (JMongoBrowser),[39] cross-platform Management-GUI, implemented in Java


According to, in November 2014, MongoDB is in 5th place as the most popular type of database management system, and first place for document stores.[2]

Production deployments

Large-scale deployments of MongoDB are tracked by MongoDB Inc. Some of the prominent users of MongoDB include:

  • MetLife uses MongoDB for “The Wall", a customer service application providing a "360-degree view" of MetLife customers.[40]
  • SAP uses MongoDB in the SAP PaaS.[41]
  • [42]
  • Shutterfly uses MongoDB for its photo platform. As of 2013, the photo platform stores 18 billion photos uploaded by Shutterfly's 7 million users.[43][44]
  • CERN uses MongoDB as the primary back-end for the Data Aggregation System for the Large Hadron Collider.[45]
  • Foursquare deploys MongoDB on Amazon AWS to store venues and user check-ins into venues.[46]
  • eBay uses MongoDB in the search suggestion and the internal Cloud Manager State Hub.[47]

See also


  1. ^ a b "10gen embraces what it created, becomes MongoDB Inc.". Gigaom. Retrieved 27 August 2013. 
  2. ^ a b "Popularity ranking of 216 database management systems". Solid IT. Retrieved 8 November 2014. 
  3. ^ The MongoDB NoSQL Database Blog, The AGPL
  4. ^ MongoDB Developer Manual
  5. ^ Data Modeling for MongoDB
  6. ^ [1]
  7. ^ [2]
  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. ^ "Default Write Concern Change". MongoDB Release Notes. Retrieved April 17, 2014. 
  13. ^ FAQ Concurrency - How Granular Are Locks
  14. ^ FAQ Concurrency - How Does Sharding Affect Concurrency
  15. ^ FAQ Concurrency - Do Operations Ever Yield the Lock
  16. ^ 32-bit Limitations
  17. ^ Does Everybody Hate MongoDB
  18. ^ Optimizing Your MongoDB Dataset
  19. ^ "memcmp". 31 May 2013. Retrieved 26 April 2014. 
  20. ^ MongoDB Jira ticket 1920
  21. ^ "MongoDB Drivers and Client Libraries". Retrieved 2013-07-08. 
  22. ^ "Community Supported Drivers". Retrieved 2014-07-09. 
  23. ^ mongo - The Interactive Shell
  24. ^ HTTP Console
  25. ^ mongostat Manual
  26. ^ mongotop Manual
  27. ^ mongosniff Manual
  28. ^ mongoimport Manual
  29. ^ mongoexport Manual
  30. ^ mongodump Manual
  31. ^ mongorestore Manual
  32. ^ "3T MongoChef". Retrieved 2014-10-01. 
  33. ^ "Fang of Mongo". Retrieved 2012-06-22. 
  34. ^ "Futon4Mongo". Retrieved 2012-06-22. 
  35. ^ "Mongo Management Studio". Retrieved 2014-09-01. 
  36. ^ "Mongo3". Retrieved 2012-06-22. 
  37. ^ "MongoHub". Retrieved 2012-06-22. 
  38. ^ "Opricot". Retrieved 2012-06-22. 
  39. ^ "UMongo". Retrieved 2012-06-22. 
  40. ^ "Metlife uses nosql for customer service". Information Week. Retrieved 8 November 2014. 
  41. ^ The Quest to Understand the Use of MongoDB in the SAP PaaS
  42. ^ Scaling SourceForge with MongoDB
  43. ^ Real World NoSQL: MongoDB at Shutterfly
  44. ^ Here's How We Think Of Shutterfly's Stock Value
  45. ^ Holy Large Hadron Collider, Batman!
  46. ^ Experiences Deploying MongoDB on AWS
  47. ^ MongoDB at eBay


  • Hoberman, Steve (June 1, 2014), Data Modeling for MongoDB (1st ed.),  
  • Banker, Kyle (March 28, 2011), MongoDB in Action (1st ed.),  
  • Chodorow, Kristina; Dirolf, Michael (September 23, 2010), MongoDB: The Definitive Guide (1st ed.),  
  • Pirtle, Mitch (March 3, 2011), MongoDB for Web Development (1st ed.),  
  • Hawkins, Tim; Plugge, Eelco; Membrey, Peter (September 26, 2010), The Definitive Guide to MongoDB: The NoSQL Database for Cloud and Desktop Computing (1st ed.),  

External links

  • Official website
  • Designing for the Cloud at MIT Technology Review
  • A vendor-independent comparison of NoSQL databases: Cassandra, HBase, MongoDB, Riak (NetworkWorld)
  • MongoDB Cheat Sheet for Quick Reference
  • Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase vs Couchbase vs Neo4j vs Hypertable vs ElasticSearch vs Accumulo vs VoltDB vs Scalaris comparison
  • How MongoDB Different Write Concern Values Affect Performance On A Single Node
  • MongoDB Fault Tolerance
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