Relational flat file

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. 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. There are, however, certain disadvantages to using relational databases. Relational databases are far more flexible though harder to design and maintain than what are known as flat file databases, which contain a single table of data.

To understand the advantages of a relational database, imagine the needs of two small companies that take customer orders for their products. Company A uses a flat file database with a single table named orders to record orders they receive, while Company B uses a relational database with two tables: orders and customers. When a customer places an order with Company A, a new record or row in the table orders is created. Because Company A has only one table of data, all the information pertaining to that order must be put into a single record.

This means that the customer's general information, such as name and address, is stored in the same record as the order information, such as product description, quantity, and price. Most relational databases offer functionality to share data:. Designing flat file databases is simple and requires little design knowledge.

Flat files can be developed using just about any database engine. Flat files can be created in relational database engines by not taking advantage of relational design concepts. Designing a relational database takes more planning than flat file databases. With flat files, you may add information, as you deem necessary. With relational databases, you must be careful to store data in tables such that the relationships make sense.

Building a relational database is dependant upon your ability to establish a relational model. However, database systems professionals commonly adopt the specific conventions of the "relational model" introduced by E. Codd of the IBM corporation in Walters, , p.

This model uses formal mathematical rules of set theory and relational algebra to arrange the tables and their relationships in a manner that prevents anomalies from occurring while data are inserted, updated, or deleted.

The guidelines for this system, called "normalization", require that every row tuple have a primary key, the attributes in a relational table must depend on the primary key, and the nonkey attributes in the table must be independent of each other. In other words, complex data systems are broken up into their most fundamental relationships to form tables, each of which must have a primary key, and which generally have less than 25 fields columns.

An example of such a relational system with minor modifications applied to sediment chemistry is provided in figure 2 and table 2 data from the U. This system allows computer database managers to manipulate very large and complex databases with flexibility and efficiency.

Normalized tables are essential in a very large database, especially one containing data that require frequent updating. A table that is not normalized may contain data that is dependent on other data or entries that are repeated, which causes significant difficulties in maintaining the internal consistency integrity of the database. The disadvantage of removing all dependencies is that these are precisely the relationships scientists use to compare and analyze data.