|Stable release||3.0.3 / 12 May 2015|
|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 10gen (now 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 10gen offering commercial support and other services. 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. As of 2014[update], MongoDB was the most popular NoSQL database system.
Licensing and support
MongoDB is available for free under the GNU Affero General Public License. The language drivers are available under an Apache License. In addition, MongoDB Inc. offers proprietary licenses for MongoDB.
Some of the features include:
- 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.
- Ad hoc queries
- 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. 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. 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, 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 and lighttpd. 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.
- 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.
- 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.
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. Since version 3.0, pluggable storage engines were introduced, and each storage engine may implement concurrency control differently. With MongoDB 3.0 concurrency control is implemented at the collection level for the MMAPv1 storage engine, and at the document level with the WiredTiger storage engine. With versions prior to 3.0, one approach to increase concurrency is to use sharding. 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.
Another criticism is related to the limitations of MongoDB when used on 32-bit systems. In some cases, this was due to inherent memory limitations. 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.
Additionally, MongoDB does not support collation-based sorting and is limited to byte-wise comparison via memcmp, which will not provide correct ordering for many non-English languages when used with a Unicode encoding.
MongoDB has official drivers for a variety of popular programming languages and development environments. There are also a large number of unofficial or community-supported drivers for other programming languages and frameworks.
Management and graphical front-ends
||This section possibly contains original research. (June 2015)|
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, 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
- HumongouS.io, 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
Large-scale deployments of MongoDB are tracked by MongoDB Inc. Notable users of MongoDB include:
- Amadeus IT Group uses MongoDB for its back-end software.
- The Compact Muon Solenoid at CERN uses MongoDB as the primary back-end for the Data Aggregation System for the Large Hadron Collider.
- eBay uses MongoDB in the search suggestion and the internal Cloud Manager State Hub.
- Foursquare deploys MongoDB on Amazon AWS to store venues and user check-ins into venues.
- LinkedIn uses MongoDB as their backend DB.
- MetLife uses MongoDB for “The Wall", a customer service application providing a "360-degree view" of MetLife customers.
- SAP uses MongoDB in the SAP PaaS.
- Shutterfly uses MongoDB for its photo platform. As of 2013, the photo platform stores 18 billion photos uploaded by Shutterfly's 7 million users.
- Sophos uses MongoDB in their cloud security technology.
- Sourceforge uses MongoDB for its back-end storage pages.
- Talentica Software uses MongoDB in Ad-serving platform for one of their client.
||This "see also" section may contain an excessive number of suggestions. Please ensure that only the most relevant suggestions are given and that they are not red links, and consider integrating suggestions into the article itself. (April 2015)|
- SpiderMonkey (software)
- Server-side scripting
- MEAN, a solutions stack using MongoDB as the database
- HyperDex, a NoSQL database providing the MongoDB API with stronger consistency guarantees
- OrientDB, a Document-Graph Multi-model database
- "10gen embraces what it created, becomes MongoDB Inc.". Gigaom. Retrieved 27 August 2013.
- "Popularity ranking of database management systems". db-engines.com. Solid IT. Retrieved 2015-07-04.
- The MongoDB NoSQL Database Blog, The AGPL
- MongoDB Developer Manual
- Data Modeling for MongoDB
- Introduction to Replication
- Introduction to Sharding
- GridFS article on MongoDB Developer's Manual
- NGINX plugin for MongoDB source code
- lighttpd plugin for MongoDB source code
- Expertstown - MongoDB overview
- Kyle Kingsbury (2015-04-20). "Call me maybe: MongoDB stale reads". Retrieved 2015-07-04.
- MongoDB Jira Ticket 4328
- Eliot Horowitz (2015-01-22). "Renaming Our Upcoming Release to MongoDB 3.0". Retrieved 2015-02-23.
-  - MongoDB 2.8 release
- MMAPv1 Concurrency Improvement
- WiredTiger Concurrency and Compression
- FAQ Concurrency - How Does Sharding Affect Concurrency
- FAQ Concurrency - Do Operations Ever Yield the Lock
- 32-bit Limitations
- Does Everybody Hate MongoDB
- "memcmp". cppreference.com. 31 May 2013. Retrieved 26 April 2014.
- MongoDB Jira ticket 1920
- "MongoDB Drivers and Client Libraries". Mongodb.org. Retrieved 2013-07-08.
- "Community Supported Drivers". Mongodb.org. Retrieved 2014-07-09.
- Presentation by Amadeus 11/2014
- Holy Large Hadron Collider, Batman!
- MongoDB at eBay
- Experiences Deploying MongoDB on AWS
- Presentation by LinkedIn
- "Metlife uses nosql for customer service". Information Week. Retrieved 8 November 2014.
- The Quest to Understand the Use of MongoDB in the SAP PaaS
- Real World NoSQL: MongoDB at Shutterfly
- Here's How We Think Of Shutterfly's Stock Value
- Scaling SourceForge with MongoDB
- Hoberman, Steve (June 1, 2014), Data Modeling for MongoDB (1st ed.), Technics Publications, p. 226, ISBN 978-1-935504-70-2
- Banker, Kyle (March 28, 2011), MongoDB in Action (1st ed.), Manning, p. 375, ISBN 978-1-935182-87-0
- Chodorow, Kristina; Dirolf, Michael (September 23, 2010), MongoDB: The Definitive Guide (1st ed.), O'Reilly Media, p. 216, ISBN 978-1-4493-8156-1
- Pirtle, Mitch (March 3, 2011), MongoDB for Web Development (1st ed.), Addison-Wesley Professional, p. 360, ISBN 978-0-321-70533-4
- Hawkins, Tim; Plugge, Eelco; Membrey, Peter (September 26, 2010), The Definitive Guide to MongoDB: The NoSQL Database for Cloud and Desktop Computing (1st ed.), Apress, p. 350, ISBN 978-1-4302-3051-9