A database can be described as relational when it has been
design to conform, or mostly conform to a set of practices known as the rules
of normalization. In order to understand
relational database, the basics of a database need to be know first. A database is typically constructed in two
different stages. The first stage is
creating a logical data model. A logical
data model allow you to lay out the design and organization of the
database. The second stage is the
creation of the physical data model. The
physical data model sets up the parts of the database visible to users, such as
columns and tables. In fact, relational
databases story highly structured tables in columns of specific types and many rows
of the same kind of information. This is
why the organization, and really the logical data model part of a relational database
is so important.
Now that you know a little about databases, it’s time to
discuss some terminology specific to relational databases. The first relational database term I am going
to discuss is entity. An entity stores
information in a database regarding something of interest in the real world,
such as departments within an organization.
Next, an attribute represents information regarding an object that will
be tracked, such as the birth date or social security number of an employee. One last crucial concept within relational
databases is a primary key. A primary
key identifies a specific instance or object of an entity, meaning no two
instances or objects can have the same primary key. A great example of a primary key in
relational databases are ID numbers, such as the IP Address of a computer.
One popular language used for querying relational databases
is SQL. SQL can be used in many
different ways for querying relational databases. For instance, one use of SQL is for read-only
operations, while other times it is used for read/write operations. This way, only certain people can make changes
to the database at certain times.
Lastly, relational databases should not get confused with
graph databases, although they can be very useful for graph databases. As neo4J states, “relationships are
first-class citizens of the graph data model, unlike other database management systems,
which require us to infer connections between entities using special properties
such as foreign keys, or out-of-band processing like map-reduce. In other words, relational databases are like
the stepping stone for graph databases.
Some people even view graph databases as an evolution of relational
databases.
References
Comments
1.) Janet Tran's Comment
2.) Laura Worley's Comment
Just from reading your article I could tell you used the dummies article since your post was organized in a similar manner to the source and did a good job of explaining the basic concepts. To make this post better I would say how it is actually used in the real world.
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