Aggregation is absolutely one of Mongo's weaknesses. It's not great at ad-hoc aggregation like MySQL or whatnot is, and the fact that it tends to lend itself to denormalized data makes SQL-style reporting clunky at best.

It does a lot of things better than SQL, too. Consider, for example, the query "Give me a list of all posts with all of these tags, by any of these authors, sorted by post date descending"

    db.posts.find({
      tags: {$all: ["foo", "bar", "baz"]},
      author: {$in: ["Joe", "Jane"]}
    }).sort({post_date: -1})

In SQL, you'd end up with something like:

    SELECT posts.* FROM posts
      INNER JOIN post_tags t1 ON t1.tag = "foo" AND t1.post_id = posts.id
      INNER JOIN post_tags t2 ON t2.tag = "bar" AND t2.post_id = posts.id
      INNER JOIN post_tags t3 ON t3.tag = "baz" AND t3.post_id = posts.id
      WHERE posts.author = "Joe" or post.author = "Jane"
      ORDER BY post_date DESC;

Its strength is denormalization; since you can denormalize entire lists or maps of data into a document, and then index and query on them, you can end up performing queries that would be ridiculously ugly and tedious in SQL.