Database Reference
In-Depth Information
Physical data modeling is the process of capturing the detailed technical solution. This
is the first time we are actually concerning ourselves with technology and technology is-
sues such as performance, storage, and security. For example, conceptual data modeling
captures the satellite view of the business requirements, revealing that a
Customer
places
many
Orders
. Logical data modeling captures the detailed business solution, which in-
cludes all of the properties of
Customer
and
Order
such as the customer's name, their
address, and the order number. After understanding both the high level and detailed busi-
ness solution, we move on to the technical solution, and physical data modeling may lead
to embedding
Order
within
Customer
in MongoDB.
In physical data modeling, we aim to build an efficient MongoDB design, addressing ques-
tions such as:
•
What should the collections look like?
•
What is the optimal way to do sharding?
•
How can we make this information secure?
•
How should we store history?
•
How can we answer this business question in less than 300 milliseconds?
P
HYSICAL
D
ATA
M
ODELING
A
PPROACH
There are five steps to physical data modeling:
