Databases Reference
In-Depth Information
Sally works on projects that need custom applications developed and she's knowledge-
able about
SQL
and NoSQL technologies. Her job is to find the best fit for the busi-
ness problem.
Now let's see how Sally applies her knowledge in two examples. In the first exam-
ple, a group that needed to track equipment warranties of hardware purchases came
to Sally for advice. Since the hardware information was already in an
RDBMS
and the
team had experience with
SQL
, Sally recommended they extend the
RDBMS
to
include warranty information and create reports using joins. In this case, it was clear
that
SQL
was appropriate.
In the second example, a group that was in charge of storing digital image infor-
mation within a relational database approached Sally because the performance of the
database was negatively impacting their web application's page rendering. In this case,
Sally recommended moving all images to a key-value store, which referenced each
image with a
URL
. A key-value store is optimized for read-intensive applications and
works with content distribution networks. After removing the image management
load from the
RDBMS
, the web application as well as other applications saw an
improvement in performance.
Note that Sally doesn't see her job as a black-and-white,
RDBMS
versus NoSQL
selection process. Sometimes the best solution involves using hybrid approaches.
1.4
Summary
This chapter began with an introduction to the concept of NoSQL and reviewed the
core business drivers behind the NoSQL movement. We then showed how the power
wall forced systems designers to use highly parallel processing designs and required a
new type of thinking for managing data. You also saw that traditional systems that use
object-middle tiers and
RDBMS
databases require the use of complex object-relational
mapping systems to manipulate the data. These layers often get in the way of an orga-
nization's ability to react quickly to changes (agility).
When we venture into any new technology, it's critical to understand that each
area has its own patterns of problem solving. These patterns vary dramatically from
technology to technology. Making the transition from
SQL
to NoSQL is no different.
NoSQL is a new paradigm and requires a new set of pattern recognition skills, new
ways of thinking, and new ways of solving problems. It requires a new cognitive style.
Opting to use NoSQL technologies can help organizations gain a competitive edge
in their market, making them more agile and better equipped to adapt to changing
business conditions. NoSQL approaches that leverage large numbers of commodity
processors save companies time and money and increase service reliability.
As you've seen in the case studies, these changes impacted more than early tech-
nology adopters: engineers around the world realize there are alternatives to the
RDBMS
-as-our-only-option mantra. New companies focused on new thinking, technol-
ogies, and architectures have emerged not as a lark, but as a necessity to solving real
