What is a Flat File?
A flat file or a sequential file is a type of file that stores data in the form of columns and rows to emulate a database table. It is like a table with a single record per line. It is also known as a text database, as it stores the data in the form of rows and columns as in RDBMS. Furthermore, international Business Machines (IBM) developed and implemented this database in the early 1970s.
Flat files use a standardized character code known as the American Standard Code for Information Exchange (ASCII) while writing data. Any type of Extract, Transform, and Load(ETL) tools or scripting language can be used to process and manipulate these ASCII-based flat files.
A flat file is equivalent to a database table with a single record per line and does not have multiple tables unlike in a relational database. It does not have any information related to structure markup or associated paths or folders. It has first rows as field names that make it easier to determine which data is being read by the application. Rows in the flat files are in the form of tuples, which is an ordered list of elements.
Below are some Examples of Flat files in which we have comma(,) and Pipe(|) as Delimiter.
NAME, ADDRESS, WEBSITE
NITENDRATECH, USA, https://www.nitendratech.com/
THE VERGE,USA, https://theverge.com/
NAME|ADDRESS|WEBSITE
NITENDRATECH|USA|https://www.nitendratech.com/
THE VERGE|USA|https://theverge.com/
Where is Flat File Used?
Flat files have a small structure and take up small space, making it easy to create, read, and maintain. They just store the table’s data without holding any relations between the tables within the files. Every column in a flat file has a restricted data type. It means we cannot have String data in the columns that are supposed to have numbers in them.
Below are Some of the use cases.
- Used for building applications
- Easy to maintain for commonly accessed information such as names, addresses, phone numbers, membership lists, or Student lists.
- Utilized on the Internet of Things (IoT) and data warehouse/data lake environments.
- Spreadsheet-based applications like Microsoft Excel and Google Sheets is used to create and manipulate flat files based databases
- Used in the management of Object oriented storage systems
Types of Flat Files?
There are many types of Flat files which vary according to their format, specific structure, and characteristics. They are distinguished by their delimiters that separate the fields or attributes within the file.
- Comma Separated Values(CSV): This flat file uses commas as field delimiters. They can be read easily through rows and columns. They are compatible with applications such as Microsoft Excel, Google Sheets, and other programming languages. In a CSV file, table data is gathered in lines of ASCII text with the value of each table cell separated by a comma, with each row represented by a new line.
- Tab Separated Values(TSV): This flat file uses tabs as field delimiters and has a format similar to CSV File. They are a better option to use if any of the data elements contain commas in the actual values. They are trendy in storing bioinformatics data and in data pipelines.
- Key-Value Pair File: These files store the data in the form of key-value pairs. They mostly have equal sign or colon as delimiters. They are mostly used in storing the configuration or properties of software applications
- Fixed Width Format: These files have a predetermined number of columns that align the data into columns, They are very popular in legacy systems like Mainframe or similar system
Advantages and Disadvantages of Flat Files
Flat files are an excellent choice for various scenarios, but might not be suitable for all scenarios. Let’s look at some of the advantages and disadvantages of Flat files.
Advantages
- Simple, Human Readable that
- It allows for easy creation and manipulation of data by both developer and non-technical users
- Platform agnostic that allows for seamless data exchange between different systems and applications
- A popular choice for tasks like data import/export, data analysis, and storing system-related configuration files.
Disadvantages
- The absence of Support for complex relations makes it unsuitable for applications with complex data structures or dependencies
- Less efficient and scalable when data is large when compared to RDBMS and NoSQL databases
- Does not support indexing, querying, or transaction control, which are essential for modern architectures involving large-scale and evolving data requirements.
- Provides limited support for data integrity and consistency as lacks support for constraint, relationship, and validation rules.
- Limitations in the number of rows, column length, and overall file size because of constraints of the Operating System(OS) or File Management system.
