Drawbacks of File Management System
- Data Redundancy – Data redundancy refers to the duplication of data, lets say we are managing the data of a Bank where a Account Holder has two Accounts. The Account Holder details in such case will be stored twice, which will take more storage than needed. Data redundancy often leads to higher storage costs and poor access time.
- Data Inconsistency – Data redundancy leads to data inconsistency, lets take the same example that we have taken above – a Account Holder has two Accounts and we stored the Account Holder’s address twice, now lets say the Account Holder requests to change his address, if the address is changed at one place and not on all the records then this can lead to data inconsistency.
- Data Isolation – Because data are scattered in various files, and files may be in different formats, writing new application programs to retrieve the appropriate data is difficult.
- Dependency on Application Programs – Changing files would lead to change in application programs.
- Atomicity Issues – Atomicity of a transaction refers to “All or nothing”, which means either all the operations in a transaction executes or none.For example: Lets say Rohit transfers Rs. 100/- to Amit’s account. This transaction consists multiple operations such as debit Rs. 100/- from Rohit’s account, credit Rs. 100/- to Amit’s account. Like any other device, a computer system can fail. Lets say it fails after first operation, then in that case Rohit’s account would have been debited by Rs. 100/- but the amount was not credited to Amit’s account, in such case the rollback of operation should occur to maintain the atomicity of transaction. It is difficult to achieve atomicity in File Management Systems.
- Data Security – Data should be secured from unauthorised access, for example a Account Holder in a Bank should not be able to see the payroll details of the Bank Employees, such kind of security constraints are difficult to apply in File Management Systems.
Advantage of DBMS over File Management System
- No Redundant Data – Redundancy removed by data normalization in DBMS. Normalization is a process of organizing the data in database to avoid data redundancy
- Data Consistency and Integrity – The main cause of data inconsistency is data redundancy. Since data normalization takes care of the data redundancy, data inconsistency also been taken care of as part of it
- Data Security – It is easier to apply access constraints in database systems so that only authorized user is able to access the data. Each user has a different set of access thus data is secured from the issues such as identity theft, data leaks and misuse of data.
- Data Sharing – File system does not allow sharing of data or sharing is too complex. Whereas in DBMS, data can be shared easily due to centralized system.
- Data Concurrency – Concurrent access to data means more than one user is accessing the same data at the same time. Anomalies occur when changes made by one user gets lost because of changes made by other user. File system does not provide any procedure to stop anomalies. Whereas DBMS provides a locking system to stop anomalies to occur.
- Data Searching – For every search operation performed on file system, a different application program has to be written. While DBMS provides inbuilt searching operations. User only have to write a small query to retrieve data from database.
- Data Integrity – There may be cases when some constraints need to be applied on the data before inserting it in database. The file system does not provide any procedure to check these constraints automatically. Whereas DBMS maintains data integrity by enforcing user defined constraints on data by itself.
- Easy Recovery – Since database systems keeps the backup of data, it is easier to do a full recovery of data in case of a failure.
