Flat File Databases: Pros and Cons
The flat file database structure was created during the earliest use of computer processing. In those days, flat files were stored on punch cards and tapes, paper as well as magnetic sheets. Due to their built-in restrictions, flat files are sequential in nature. As explained by marketing strategist, Alec Burke, “Think of flat files as being similar to the files in a file cabinet drawer—a collection of single records each containing standalone data.” (https://bizfluent.com). Databases are made up of tables; when there is only a single table in a database, it is referred to as a flat file.
(Image above is an example of a flat-file database model courtesy of SmartSheet.com)
A flat file database is an efficient method when it comes to storing a limited number of records. An Excel spreadsheet, in which each row is a record and each column is a field, can be considered a flat file. There are certain advantages to such methods of data storage. For one thing, all the records can be stored in one place. They are also easy to set up, without needing specific expertise, and can be easily understood. Since they are independent, self-contained files, they require no outside storage configurations, and can be readily edited and accessed. Flat files are often used to keep track of a company’s day-to-day concerns, such as business contacts and lists of customers.
However, flat file databases have some major disadvantages and are generally not effective for large-scale record-keeping. Some problems that can arise with their use include the possibility of duplication and the difficulty of keeping records unique. This can lead to wasted storage and levels of inefficiency. Furthermore, it can be difficult to make changes in the format of the data entered, and in the retrieval of any data requiring multiple queries.
Relational Databases: Pros and Cons
Relational databases were developed to get past the limitations inherent in a simple flat file. While a flat file contains only a single table, a relational database stores data in multiple tables, consisting of columns of key values and stored values, enabling the possibility of relating one table to another. Relational databases require a structure to contain them, referred to as a server, in order to store and to interpret data. They also depend on specific tools to view and to interpret the information contained in them. In relational databases, information is stored in a randomized manner, only to be organized on retrieval. As opposed to flat files, relational databases can address more dynamic queries.
(Image above is an example of a relational database model courtesy of SmartSheet.com)
There are many advantages to relational databases. Data only needs to be stored a single time, which can eliminate duplication, resulting in a more efficient storage method as well as create an ease in making changes to the data and the data format. It can also provide an increased level of security, due to the possibility of splitting data into separate tables, limiting access to authorized viewers. Thus, “…a receptionist would be able to view employee location and contact details but not their salary. A salesman may see his team’s sales performance but not competing teams.” (https://www.teach-ict.com)
There are, however, certain disadvantages to using relational databases. For one thing, since they tend to be complex structures, they require specific skill sets to use, and often require prior training. They are also expensive, necessitating the additional purchase of software and/or licenses. According to marketing manager, Adam Hughes, “The database ultimately adopted will largely depend on the nature and purpose of the data, the database access requirements, any cost/budget variations, company in-house technical expertise, and knowledge of the other applications needing to access the database.” (https://www.cleo.com)