Difference between file based Approach and Database Approach

The key difference between file based approach and database approach is that in the file-based approach data is stored in separate files, often leading to redundancy, limited sharing, and challenges in maintaining data integrity.

In the database approach data is organized in structured tables within a Database Management System, enabling efficient querying, reduced redundancy, data integrity enforcement, and multi-user data sharing.

image showing the file base vs database approach

In this article, we will discuss the difference between the file base and database approaches and also give deep insight into both of them separately.

What is File-based Approach?

The file-oriented approach is a method of managing and organizing data in which information is stored in separate files, often organized in a hierarchical or flat structure.

Each file typically contains a specific type of data related to a particular application or aspect of the system. In this approach, data is managed directly by the applications themselves, without the use of a centralized system to oversee data storage and retrieval.

What is Database Approach?

The database approach is a method of managing and organizing data using a specialized software system known as a Database Management System (DBMS).

This approach provides a structured and centralized way to store, retrieve, manipulate, and manage large volumes of data efficiently and securely.

The fundamental idea behind the database approach is to create and maintain a single, integrated repository of data that can be shared and accessed by multiple users and applications.

File based Approach vs Database Approach

The main differences between file-based approach and the database approach are given below:

AspectFile-Oriented ApproachDatabase Approach
Data StorageFiles stored in a hierarchical or flat structure, often application-specificData stored in tables with structured rows and columns
Data RedundancyHigh potential for data redundancyReduced data redundancy through normalization
Data IntegrityChallenging to enforce data integrityEnforced data integrity through constraints and transactions
Data SharingLimited data sharing between applicationsEnables data sharing and collaboration among applications
ScalabilityLimited scalability for large datasetsDesigned for efficient management of large datasets
QueryingLimited querying capabilitiesPowerful querying using SQL (Structured Query Language)
Control and ComplexitySimple implementation and controlMore complex setup and management
Concurrent AccessLimited support for concurrent accessSupports concurrent access by multiple users
CostGenerally lower initial costsHigher initial costs due to software and setup
PerformanceEfficient for small-scale operationsOptimized performance for various operations

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