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.
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 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.
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.
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 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 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.
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, 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. 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 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.
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
In a MongoDB installation the following commands are available:
Administrative information can also be accessed through a web interface, a simple webpage that serves information about the current server status. By default, this interface is 1000 ports above the database port (28017).
mongostat 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 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 utility.
mongosniff 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 is a command-line utility to import content from a JSON, CSV, or TSV export created by mongoexport or potentially other third-party data exports.
mongodump is a command-line utility for creating a binary export of the contents of a Mongo database; mongorestore can be used to reload a database dump.
According to db-engines.com, in November 2014, MongoDB is in 5th place as the most popular type of database management system, and first place for document stores.
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.