Use Cases

See also the Production Deployments page for a discussion of how companies like Disqus, EA, Github, SourceForge, etc. use MongoDB.

Use Case Articles

• Using MongoDB for Real-time Analytics
• Using MongoDB for Logging
• Full Text Search in Mongo

Well Suited

• Operational data store of a web site. MongoDB is very good at real-time inserts, updates, and queries. Scalability and replication are provided which are necessary functions for large web sites' real-time data stores
• Caching.  With its potential for high performance, MongoDB works well as a caching tier in an information infrastructure.  The persistent backing of Mongo's cache assures that on a system restart the downstream data tier is not overwhelmed with cache population activity.
• "High volume, low value data".  Problems where a traditional DBMS might be too expensive for the data in question.  In many cases developers would traditionally write custom code to a filesystem instead using flat files or other methodologies.
• Problems requiring high scalability.  Mongo is well suited to problems where the database must comprise tens or hundreds of servers.  Map/Reduce engine integration is planned in the Mongo roadmap.
• Storage of program objects and JSON data (and equivalent).  Mongo's BSON data format makes it very easy to store and retrieve data in a document-style / "schemaless" format. Addition of new properties to existing objects is easy and does not require blocking "ALTER TABLE" style operations.

Less Well Suited

• Highly transactional systems, such as banking systems and accounting.  MongoDB, like most "NOSQL" solutions, provides lightweight transactionality: atomicity around single documents only. Applications with highly complex transactions are more suited to a traditional RDBMS.
• Traditional Business Intelligence.  Data warehouses are more suited to new, problem-specific BI databases.  However note that MongoDB can work very well for several reporting and analytics problems where data is predistilled or aggregated in runtime -- but classic, business intelligence is not a sweet spot.
• Problems requiring SQL.