We can also index the embedded document as a whole, similar 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:

> 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.