Databases Reference
In-Depth Information
and case studies are targeted toward technical managers, solution architects, and data
architects who are interested in learning about NoSQL.
This material will help you objectively evaluate
SQL
and NoSQL database systems
to see which business problems they solve. If you're looking for a programming guide
for a particular product, you've come to the wrong place. Here you'll find informa-
tion about the motivations behind NoSQL, as well as related terminology and con-
cepts. There may be sections and chapters of this topic that cover topics you already
understand; feel free to skim or skip over them and focus on the unknown.
Finally, we feel strongly about and focus on
standards
. The standards associated
with
SQL
systems allow applications to be ported between databases using a common
language. Unfortunately, NoSQL systems can't yet make this claim. In time, NoSQL
application vendors will pressure NoSQL database vendors to adopt a set of standards
to make them as portable as
SQL
.
In this chapter, we'll begin by giving a definition of NoSQL. We'll talk about the
business drivers and motivations that make NoSQL so intriguing to and popular with
organizations today. Finally, we'll look at five case studies where organizations have
successfully implemented NoSQL to solve a particular business problem.
1.1
What is NoSQL?
One of the challenges with NoSQL is defining it. The term
NoSQL
is problematic since
it doesn't really describe the core themes in the NoSQL movement. The term origi-
nated from a group in the Bay Area who met regularly to talk about common con-
cerns and issues surrounding scalable open source databases, and it stuck. Descriptive
or not, it seems to be everywhere: in trade press, product descriptions, and confer-
ences. We'll use the term NoSQL in this topic as a way of differentiating a system from
a traditional relational database management system (
RDBMS
).
For our purpose, we define NoSQL in the following way:
NoSQL is a set of concepts that allows the rapid and efficient processing of data sets with
a focus on performance, reliability, and agility.
Seems like a broad definition, right? It doesn't exclude
SQL
or
RDBMS
systems, right?
That's not a mistake. What's important is that we identify the core themes behind
NoSQL, what it is, and most importantly what it isn't.
So what is NoSQL?
It's more than rows in tables
—NoSQL systems store and retrieve data from many
formats: key-value stores, graph databases, column-family (Bigtable) stores, doc-
ument stores, and even rows in tables.
It's free of joins
—NoSQL systems allow you to extract your data using simple
interfaces without joins.
It's schema-free
—NoSQL systems allow you to drag-and-drop your data into a
folder and then query it without creating an entity-relational model.
