Database Reference
In-Depth Information
With this custom-made map, which contained only the information that was relevant to me,
I arrived at my address without making a single wrong turn. The map was a model of the
actual roads I needed to travel.
Now, what does my poor sense of direction and a gas station attendant skilled at drawing
maps have to do with MongoDB? A map simplifies a complex
geographic
landscape in
the same way that a data model simplifies a complex
information
landscape. In many cases
with large data volumes, high velocity in receiving data, and diverse data types, the com-
plexities we encounter in MongoDB applications can make those roundabouts in France
look ridiculously simple. We therefore need maps (in the form of data models) to provide
clear and precise documentation about an application's information landscape.
It would probably have taken me hours of trial and error to reach my destination in France,
whereas that simple map the gas station attendant drew provided me with an almost instant-
aneous broad understanding of how to reach my destination. A model makes use of stand-
ard symbols that allow one to grasp the content quickly. In the map he drew for me, the
attendant used lines to symbolize streets and circles to symbolize roundabouts. His skillful
use of those symbols helped me visualize the streets and roundabouts.
Data modeling is the process of learning about the data, and the data model is the end result
of the data modeling process. A data model is a set of symbols and text that precisely ex-
