Databases Reference
In-Depth Information
1.2.4
Agility
The most complex part of building applications using
RDBMS
s is the process of putting
data into and getting data out of the database. If your data has nested and repeated
subgroups of data structures, you need to include an object-relational mapping layer.
The responsibility of this layer is to generate the correct combination of
INSERT
,
UPDATE
,
DELETE
, and
SELECT
SQL
statements to move object data to and from the
RDBMS
persistence layer. This process isn't simple and is associated with the largest bar-
rier to rapid change when developing new or modifying existing applications.
Generally, object-relational mapping requires experienced software developers
who are familiar with object-relational frameworks such as Java Hibernate (or NHiber-
nate for .Net systems). Even with experienced staff, small change requests can cause
slowdowns in development and testing schedules.
You can see how velocity, volume, variability, and agility are the high-level drivers
most frequently associated with the NoSQL movement. Now that you're familiar with
these drivers, you can look at your organization to see how NoSQL solutions might
impact these drivers in a positive way to help your business meet the changing
demands of today's competitive marketplace.
1.3
NoSQL case studies
Our economy is changing. Companies that want to remain competitive need to find
new ways to attract and retain their customers. To do this, the technology and people
who create it must support these efforts quickly and in a cost-effective way. New
thoughts about how to implement solutions are moving away from traditional meth-
ods toward processes, procedures, and technologies that at times seem bleeding-edge.
The following case studies demonstrate how business problems have successfully
been solved faster, cheaper, and more effectively by thinking outside the box. Table 1.2
summarizes five case studies where NoSQL solutions were used to solve particular busi-
ness problems. It presents the problems, the business drivers, and the ultimate findings.
As you view subsequent sections, you'll begin to see a common theme emerge: some
business problems require new thinking and technology to provide the best solution.
Table 1.2 The key case studies associated with the NoSQL movement—the name of the case study/
standard, the business drivers, and the results (findings) of the selected solutions
Case study/standard
Driver
Finding
LiveJournal's Memcache
Need to increase performance
of database queries.
By using hashing and caching, data in
RAM can be shared. This cuts down the
number of read requests sent to the
database, increasing performance.
Google's MapReduce
Need to index billions of web
pages for search using low-cost
hardware.
By using parallel processing, indexing
billions of web pages can be done
quickly with a large number of commod-
ity processors.
