File-oriented approach VS Database approach

One of the first lectures of my Database design class was the explanation of the differences between the file-oriented approach and the database approach when dealing with the storage and manipulation of data.

In a nutshell, we can say distinguish between the following advantages VS disadvantages.
But first, what is file-oriented approach? That's an "old" system where files are stored separately and each one of them is independent from the others. On the other side, a database approach allows us to associate data and keep and interdependent system.

File-oriented approach disadvantages

• Data redundancy. There will be duplicates, as the files are created independently.
• This increases maintenance costs
• And also leads to data inconsistency, due to duplicates and/or similar data stored in different formats.
• Lack of data integration. This means we cannot associate data, as there are no association mechanisms.
• Program/data dependence to the physical format (the files themselves)
• Lack of flexibility. This means we are very limited on what we can do with our data:
• Limited information retrieval options
• Can only use pre-programmed reports

Database approach

Advantages

• Elimination of data redundancy, as we now have mechanisms to avoid duplicates.
• Now we have the ability to associate data, of course, like the relational model.
• Data is independent from the program used
• Usually, we'll enjoy better interfaces for managing the data
• More security and enforcement of integration of data

Disadvantages

• DBMS (DataBase Management Systems) are more complex to use than simply accessing isolated files
• The computers will need more resources 

Types of Database models

The Database approach is not one single entity which only works using a single model, we have several models.

• Hierarchical model. It follows a tree structure, 1:N, which means one-to-many. Each record can only have one parent. This is an old model with little use today. It cannot deal with data redundancy.
• Network model. Yes, this allows M:N, which means many-to-many relationships. Think about a typical business' departments organigram. One advantage of this model is that it can deal with data redundancy.
• Relational model. Which is made from 2-dimensional tables with implicit relationships. It is the most common today and some languages as SQL work under this model
• Important keywords/definitions of this model
• Tuple = row/record
• Attribute = column/field
• Cardinality = number of rows
• Degree = number of columns
• PK (Primary Key)  = unique identifier
• Domain = pool of legal values
• Post-relational models. In the recent years we have seen some efforts to develope other models for managing and processing more general data.