We can also index the embedded document as a whole in a similar way to indexing embedded fields:

> db.books.createIndex( { "meta_data": 1 } )

Here, we are indexing the whole document, expecting queries against its entirety like the following one:

> db.books.find({"meta_data": {"page_count":256, "average_customer_review":4.8}})

The key difference is that when we index embedded fields we can perform range queries on them using the index, whereas when we index embedded documents we can only perform comparison queries using the index.