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Lesson 2 Relational vs. flat file databases
ObjectiveUnderstand the Difference between Relational and Flat File Databases.

Understand Difference between Relational Databases and Flat Files

Relational databases and flat file databases represent two distinct paradigms for data storage and management, each with its own set of characteristics, advantages, and use cases. Understanding the fundamental differences between these two types of databases is essential for evaluating their suitability for various applications.
Relational Databases:
Relational databases are built upon the relational model, a framework proposed by E.F. Codd in 1970. This model organizes data into one or more tables (or "relations") of columns and rows, with a unique key identifying each row. Rows in one table can relate to rows in another table through the use of foreign keys, establishing a dynamic and flexible relationship between datasets. This structure allows for complex querying and analysis, making relational databases particularly well-suited for handling large volumes of data that require robust transactional integrity and complex relationships between data entities. The relational database management systems (RDBMS) support Structured Query Language (SQL), a standardized language for managing and manipulating data. SQL enables users to perform a wide range of operations, such as querying, updating, inserting, and deleting data, as well as managing database schemas and access controls. RDBMSes often provide extensive features for concurrency control, data integrity, and recovery mechanisms to ensure the consistency and reliability of data.

Flat File Databases:
In contrast, flat file databases store data in a single table or file, often structured as a plain text file where each line represents a record and fields are separated by delimiters, such as commas or tabs. This simplicity lends itself to straightforward data storage and is easily understandable and accessible by both humans and computer programs without the need for complex database management software. However, the simplicity of flat file databases also introduces limitations. They lack the ability to efficiently manage relationships between different datasets, as all data is stored in a single table. This can lead to data redundancy and inconsistency, making flat file databases less suitable for applications that require complex data relationships or transactional operations. Moreover, flat file systems do not support advanced querying capabilities inherent to SQL, limiting the complexity of data manipulation and retrieval that can be performed.

Comparative Analysis:
The choice between relational databases and flat file databases largely depends on the specific requirements of the application. Relational databases offer powerful capabilities for managing complex data relationships, integrity, and consistency, making them ideal for enterprise-level applications and systems that require complex data analysis, reporting, and transaction management. On the other hand, flat file databases are well-suited for smaller, simpler applications where data relationships are minimal, and the overhead of a relational database system is unnecessary or undesirable.
In summary, while relational databases provide a robust framework for complex data management and analysis, flat file databases offer a simpler, more lightweight approach to data storage. The decision to use one over the other should be informed by the specific data management needs and the complexity of the data relationships within the application domain.

History of Flat Files and Flat File Database

Flat files date back to the earliest days of computer processing. Originally flat files were stored on punch cards, paper tape, or magnetic tape and these are inherently sequential. Flat files are still widely used, even for files stored on a disk. One reason why flat files are still used, is that sequential access is faster than indexed access, (also known as random access or direct access). Flat files are often used to transmit data between batch processing systems, especially on mainframes.
A flat file database contains information that, as often as possible, is stored in the order in which it is needed. The approach of a flat file database is contrary to the approach of a relational database, in which how information is stored does not matter; how it is retrieved does. Flat files use techniques such as keeping track of pointers from one set of information to another. These pointers, called linked lists in many approaches, are difficult for the developer to maintain. Any time someone adds information to the database, the pointers have to be updated to show the next piece of information and the previous set of information. The management of these pointer updates is challenging for database developers when working with legacy flat file technology. Relational databases do not use flat file approaches. Instead, relational databases focus on storing information efficiently for the operating system and database package. This is separate from the emphasis on providing a means for easy information retrieval from the system. Data can be accessed or organized in different ways without the need to make accompanying changes to the tables.
Prior to using SQL, typical systems used a flat file approach. A flat file is a computer file that can
  1. only be read or written sequentially,
  2. consists of one or more records,
  3. Each record contains one or more field instances,
  4. Each field instance can contain a data value, or be omitted.

Some definitions state that all records must be of the same type and this restriction is usual when discussing a flat file database. However, most usages allow a flat file to have more than one record type.

Characteristics of Flat Files

A flat file is like a large container of all your data, similar to a single table where you store all the data. The data can be structured in nature consisting of multiple rows and columns with each column corresponding to an attribute. For example, a single record can be written into the flat file as multiple data items delimited with space or comma. A CSV file is a good example of a flat file to store records as an in the case of an email list. Usually you will store fixed size records in a flat file. One disadvantage of a flat file is that it does not give you any structure or relations if you are planning to build a database with multiple flat files. On the other hand, with a RDBMS, one can
  1. relate multiple tables,
  2. create parent child relationships,
  3. enforce constraints,
  4. index the data of a particular table.
In the case of a flat file, users will be directly working on the flat file. They will consider a flat file as a single container of all the data and will potentially work with read()/write()/ and seek() operations to access and manipulate data records in the file. If we are planning to implement a table like concept, then it has to be done at the file level where we say that each flat file corresponds to a single table.

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