Building Node Applications with MongoDB and Backbone

Chapter 4. MongoDB

When it comes to NoSQL databases, it is hard to beat the ease of use offered by MongoDB. Not only is it well documented and supported by a large and helpful community, but it is friendly to developers coming from an SQL background—many queries and a great deal of relational thinking can be directly applied from SQL to MongoDB—making it an especially attractive system for newcomers to the NoSQL world.

In relational databases, a single entity is stored in a row with a series of columns. Because entities are defined in a strict schema, every row will have the same columns. Working with entities involves comparing columns with very little overhead: all of the data is the same by design. In MongoDB there is no strictly defined schema and there are no rows containing columns—instead, every entity is stored in a document with any number of fields.

Documents provide a lot of power; you can store much more related information about each entity inside the document, even putting lists of documents inside other documents. Instead of making multiple queries to the database to get a complete set of information (as you would have to do with an SQL database), you can load entire datasets in a single operation.

Accessing Data

Not only is MongoDB friendly to developers coming from an SQL background, but its website goes out of its way to show how many SQL statements can be converted to MongoDB queries. In any database system, the end goal is always writing data—usually, persisting ...