Databases Reference
In-Depth Information
tectural design to reducing data services costs. We've demonstrated how these simple
and versatile structures can and are used to solve a broad range of business problems
for organizations having similar as well as different business requirements. As you
attack your next business problem, you'll be able to determine whether a key-value
store is the right solution.
Now that you understand the key-value store, let's move to a similar and more com-
plex data architecture pattern: the graph store. As you move through the graph store
section, you'll see some similarities to the key-value store as well as different business
situations where a using a graph store is the more appropriate solution.
4.2
Graph stores
Graph stores are important in applications that need to analyze relationships between
objects or visit all nodes in a graph in a particular manner (graph traversal). Graph
stores are highly optimized to efficiently store graph nodes and links, and allow you to
query these graphs. Graph databases are useful for any business problem that has
complex relationships between objects such as social networking, rules-based engines,
creating mashups, and graph systems that can quickly analyze complex network struc-
tures and find patterns within these structures.
By the end of this section, you'll be able to identify the key features of a graph
store and understand how graph stores are used to solve specific business problems.
You'll become familiar with graph terms such as nodes, relationships, and properties,
and you'll know about the published
W3C
standards for graph data. You'll also see
how graph stores have been effectively implemented by companies to perform link
analysis, use with rules and inference engines, and integrate linked data.
4.2.1
Overview of a graph store
A
graph store
is a system that contains a sequence of nodes and relationships that, when
combined, create a graph. You know that in a key-value store there two data fields: the
key and the value. In contrast, a graph store has three data fields:
nodes
,
relationships
,
and
properties
. Some types of graph stores are referred to as
triple stores
because of their
node-relationship-node structure (see figure 4.10).
In the last section, you saw how the structure of a key-value store is general and can
be applied to many different situations. This is also true of the basic node-relationship-
node structure of a graph store. Graph
stores are ideal when you have many items
that are related to each other in complex
ways and these relationships have properties
(like a sister/brother of). Graph stores allow
you to do simple queries that show you the
nearest neighboring nodes as well as queries
that look deep into networks and quickly
find patterns. For example, if you use a
Node
Relationship
Node
Properties
Properties
Properties
Figure 4.10
A graph store consists of many
node-relationship-node structures. Properties
are used to describe both the nodes and
relationships.
