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For problems that fit the document database model, MongoDB is now the most popular choice. In addition to ease of use and a solid technical implementation, the community and ecosystem contributed to this success. We are aware of problems where teams were tempted by the popularity of MongoDB when a document database was not a good fit or they did not understand the inherent complexity. When used appropriately, however, MongoDB has proven itself on many projects.

For problems that fit the document databases model, MongoDB provides easy programmability, a query interface, high availability with automated failover, and automated sharding capabilities. It allows for a smooth transition to NoSQL data stores from the RDBMS model, with the inclusion of familiar concepts, such as the ability to define indexes.

Document-oriented databases treat each record as a document with the ability to add any number of fields of arbitrary size. A relatively large amount of the attention that has been directed at document databases has landed on mongoDB, a highly scalable option with support for querying, indexing, replication and sharding. Beyond its enterprise feature set, its popularity is aided by its driver support for Java, Ruby, PHP, C#, Python and a number of other languages.