Aggregation Commands Comparison¶
The following table provides a brief overview of the features of the MongoDB aggregation commands.
Designed with specific goals of improving performance and usability for aggregation tasks.
See Aggregation Pipeline Operators for more information on the pipeline operators.
|Implements the Map-Reduce aggregation for processing large data sets.||
Provides grouping functionality.
Pipeline operators can be repeated as needed.
Pipeline operators need not produce one output document for every input document.
Can also generate new documents or filter out documents.
In addition to grouping operations, can perform complex aggregation tasks as well as perform incremental aggregation on continuously growing datasets.
See group for information and example using the keyf function.
Limited to the operators and expressions supported by the aggregation pipeline.
However, can add computed fields, create new virtual sub-objects, and extract sub-fields into the top-level of results by using the $project pipeline operator.
See mapReduce for details and restrictions on the functions.
See group for details and restrictions on these functions.
Returns results in various options (inline as a document that contains the result set, a cursor to the result set) or stores the results in a collection.
The result is subject to the BSON Document size limit if returned inline as a document that contains the result set.
Changed in version 2.6: Can return results as a cursor or store the results to a collection.
|Returns results in various options (inline, new collection, merge, replace, reduce). See mapReduce for details on the output options.||
Returns results inline as an array of grouped items.
The result set must fit within the maximum BSON document size limit.
The returned array can contain at most 20,000 elements; i.e. at most 20,000 unique groupings.
|Sharding||Supports non-sharded and sharded input collections.||Supports non-sharded and sharded input collections.||Does not support sharded collection.|
|More Information||See Aggregation Pipeline and aggregate.||See Map-Reduce and mapReduce.||See group.|