No, it’s not really SQL. Its syntax resembles JSON. It returns a collection of JSON documents. But the Aggregation Framework addresses for MongoDB what many have found lacking in non-relational databases, the capability for ad hoc queries that SQL performs so well.
Actually, MongoDB already supports a variety of query mechanisms: queries on object properties, regular expression queries, and complex queries using JavaScript methods. And for those aggregation queries for which a SQL developer would use a group by clause, a developer using MongoDB could use MongoDB’s built-in facilities for MapReduce, a programming pattern for grouping data into buckets and iterating through each bucket.
But JavaScript-based queries require a developer to write a function. And MapReduce requires two functions, one for the map (grouping) and one for the reduce (analysis of the group). While doable, it is quite a bit of work compared to the ease of SQL. And it is this problem that the Aggregation Framework addresses.
The Aggregation Framework provides a declarative syntax for creating query expressions. The declarative statements work together like piped commands on a UNIX shell. The statements very much resemble their SQL counterparts. There is a match statement to identify records for inclusion, a sort statement for sorting, and a group statement for grouping. Grouping supports all of the aggregation functions one would expect: average, first, minimum, maximum. And there are all of the string and date extraction statements similar to SQL.
I found the unwind statement particularly interesting. Unwind pulls out elements from an array. MongoDB documents are JSON objects, which may include a hierarchy of child objects, including arrays of objects. The unwind statement returns a copy of the parent document for each element within the child array, but instead of the entire array, each document displays only the value of one array element. The result looks much like you would expect from a SQL join.
The Aggregation Framework is not yet included in MongoDB, though it is targeted for inclusion in version 2.2 due out in March. Last night at the SF Bay MongoDB Meet-up, Chris Westin of 10gen gave a preview and demo to the crowd. For more information, see his slide deck at http://www.slideshare.net/cwestin63/mongodbs-new-aggregation-framework.
For any organization considering NoSQL databases, the Aggregation Framework will certainly ease the SQL to NoSQL transition.
Jim Downey 
The MongoDB driver for XQuery also enables complex processing such as group by or windowing. An example can be found at http://28.io/mongodb