This is the starting guide for Sparksee graph database. We will guide you during the creation of your first Sparksee graph, from downloading Sparksee to the execution of your graph. It should not take you much time but if you want to start faster, download Sparksee, download the example and run it now!.
If you are not familiar with graph databases or graph concepts, please visit this article.
The first thing you should know about the Sparksee graph you are going to build is that we define it as a labeled and directed attributed mutigraph. It is labeled because all the nodes and edges can have a type (a label) to classify them; directed because it supports edges with direction from the tail node to the head node, of course we support undirected edges too!; attributed because both nodes and edges can have one or more properties; and, finally, it is a multigraph because there are no restrictions on the number of edges between two nodes.
Figure 1 is an example of a Sparksee multigraph. Here there are two types of nodes (PEOPLE represented by a star icon and MOVIE shown as a clapperboard icon) which both have an attribute (called respectively NAME and TITLE) with a value for each of them. For instance you can see a Scarlett Johansson (NAME) node which will be of type PEOPLE (star icon). Also we can see two types of edges (DIRECTS shown in blue and CAST shown in orange). A directed edge has an arrow pointing to its head node (DIRECTS), while an undirected edge does not have any arrows (CAST). As many attributes as desired could be added to both edges and nodes.
Figure 1 above illustrates the Sparksee labeled and directed attributed multigraph definition. It has labels, as nodes and edges have types, is directed because edge DIRECTS has a certain direction and is a multigraph because node Woody Allen with node Manhattan, for instance, has two edges.
Following the steps in this guide will help you construct the graph illustrated in Figure 1.
It is also relevant to know that Sparksee is an embedded database, so from this point on, you should take into account the fact that installation and deployment of your graph database has to be made considering your programming language preference and framework.