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Database Development

The history of database development may sound like a fast trip to boredom, but it's actually much more interesting than you might think. The landmark paper was published in 1969 by E.F. Codd, proposing the relational model for databases that has remained the standard ever since. In a nutshell, the relational model separates the logical organization of the database from the physical storage method.

An introductory course in database development will most likely contain the following topics. Notice the prevalence of the word "relational" in these topics.

  • Relational Databases
  • Database Management
  • SQL Query Formulation
  • Application Development
  • Database Development
  • Modeling Data
  • Relational Table Normalization
  • Integration and Design
  • Design of Physical Databases
  • Database Administration
  • Transaction Management
  • Data Warehouse Technology/Management
  • Client-Server Processing
  • Distributed Databases
  • Object Database Management Systems

A good place to stay up to date on database developments is by visiting Database Journal. This website seems to be where the action is.

Relational Databases

The core of every application architecture is some kind of data store, because only through these data stores can we achieve persistence in our applications.  This is the backbone of every website and application in software, whether it's a customer/orders database on an e-store, posts on a forum, or files in an operating system.  It is the job of data architects, developers, and database administrators to work out the best ways to model and store information in these data stores.

Database systems can follow a number of different models.  One such model is the relational model, and it is commonly found as the back end component on websites.  This can be contrasted to the naïve concept of a ‘flat file’ database, which in its extreme could be represented in a simple spreadsheet.  There are similarities between both: a table has columns and rows, much like a spreadsheet, where columns define headings and rows define entities within your database.  At the intersection of each row and column, therefore, we find a single property defining that entity.  In a relational model, a single entity has a single dedicated row.  For instance, let’s imagine we run a web store.  A ‘Customer’ table would have 1 row for each customer.  The columns then would describe different attributes of those customers.  For example:

ID   | NAME        | PHONE    | STATE | EMAIL        


1    | Bob Smith   | 123-4567 | NY    |

It is important to note that there is a unique identifier (the ID) on the row.  This is because these attributes are not unique: a phone number might have multiple customers, and names are not unique either.  For instance, let’s say Bob’s wife Alice lives at the same address and makes an order from our company.  She too is a customer but has the same phone number as Bob.  Similarly, another customer with a different address might also be called Bob Smith.  It wouldn’t do if we could not store customers with identical attributes in our database due to these collisions.  As a result, our ID is what’s known as a primary keyThis allows our database to look as follows:

ID   | NAME        | PHONE    | STATE | EMAIL              


1    | Bob Smith   | 123-4567 | NY    |      

2    | Alice Smith | 123-4567 | NY    |    

3    | Bob Smith   | 765-4321 | TX    |

However, our database would be useless if it could only contain customer information.  We also need products to sell to our customers:



1           | Big Widget         | $30.00

2           | Small Widget       | $10.00

Again, our ID (here PRODUCT_ID) is unique.  It is conceivable we may have multiple products of the same name (perhaps to sell in different regions) or multiple products at the same price, and so we instead need to be able to generate these artificial, unique identifiers.

Finally we must consider how to actually implement the relationship between customers and products.  Customers will be able to make orders of any of our products, and clearly we cannot model orders as part of customers or products, as they are another independent entity.  Instead, we must build a table to model orders.  This makes use of a new concept: Foreign keys.  Foreign keys are references to primary keys from other tables.  They have the same values but are no longer constrained by uniqueness.  As a result, we can say that one customer has multiple products in an order, like so:



1        | 1           | 1          | 3       

1        | 1           | 2          | 1       

Note that we have two rows.  These indicate that customer id 1 (Bob) has placed an order for 3 large widgets (product id 1) and 1 small widget (product id 2).  They share an order number, because it is a single order.  We could just as easily represent multiple orders by the same person, because there isn’t a unique key for this table.

These entity relationships are often represented graphically in what’s known as an Entity Relationship Diagram.  Below is a simple example which reflects our examples above.  Pay attention to the "crow’s feet" that show which side of the relationship is 'one' and which is 'many' – for instance, one customer has many orders.  Likewise, one order has many products.

Knowing how to model and represent data entities in such relationship diagrams is a core skill used in both academic and commercial development.  Databases excel at the manipulation and storage of large volumes of data, and can quickly become impossibly complex.  Only through understanding these core concepts can one succeed in the field of data architecture or database administration.

To fulfill our mission of educating students, our online tutoring centers are standing by 24/7, ready to assist students who need extra practice in any aspect of database development.

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