File and Database Storage Systems in System Design
Last Updated :
16 Oct, 2023
In system design, File and Database Storage Systems play a pivotal role in managing and organizing data efficiently. These systems provide the foundation for storing, retrieving, and organizing information in applications, ensuring data integrity and accessibility. File systems handle structured and unstructured data, while database systems offer structured data management with advanced querying capabilities. Effective integration of these storage systems is essential for designing scalable and reliable software applications, making them integral components of modern system architecture.
Important Topics for File and Database Storage Systems in System Design
File-based storage system
File-storage/file-level/file-based storage is an effective hierarchical approach used to store data in an organized way on a computer hard drive or on a Network Attached Storage (NAS) device. Initially, the data (to be stored) is stored in files. Next, the files are organized in folders under a hierarchy of directories and subdirectories. To locate a saved file on a computer system, all one requires is a path i.e. from directory to subdirectory and to folder to file.
Examples: cloud-based file storage systems, network drives, computer hard drives, and flash drives.
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Files can be easily accessed by a user on a small scale and can be easily managed.
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Maintaining and retrieving a large number of files can be challenging.
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Most users are familiar with it.
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It is hard to work with unstructured data and becomes expensive at large levels.
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Database file-based storage system
A Database file-based storage system is a type of database management system (DBMS) storing data in files on a computer’s file system. They include a data file system for database data files and a Reco file system for storing archive files and backups. Although file-based databases are simpler and easier to manage than relational databases at the same time they are also less powerful and scalable.
Examples: Microsoft Access, SQLite, FlatfileDB etc.
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It is simple to set up and manage and relatively inexpensive.
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It is not as powerful or flexible as relational databases and has limited scalability.
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Performance rate for small datasets is good.
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Managing large datasets might be difficult for the users.
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It is portable.
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The system is vulnerable to data corruption and loss.
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The Hadoop Distributed File System (HDFS) is the primary data storage system used by Hadoop applications. Besides storing such huge data, the files are stored across multiple machines in redundant fashion to rescue the system from possible data losses in case of failure. Unlike other distributed systems, HDFS is highly fault-tolerant and designed using low-cost hardware.
Key components of HDFS are as follows:
- NameNode
- DataNode
- Secondary Name Node
- Standby Name Node
RDBMS stands for Relational Database Management System, based on the relational model introduced by E.F. Codd. It stores data in the form of tables ( having rows, columns and tuples) with the help of Structured Query Language (SQL) to access the database. All modern database management systems like SQL, MS SQL Server, IBM DB2, ORACLE, My-SQL, and Microsoft Access are based on RDBMS.
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RDBMS makes use of a table in which the headers serve as column names and the rows carry the relevant data.
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In file-based system files are organized in folders under a hierarchy of directories and subdirectories
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SQL is the standard language used to manipulate data in RDBMS.
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In a file based system data is manipulated by File APIs.
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Scalability is high.
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Scalability is low.
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Performance rate is overall good.
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Performance rate is good for small datasets but poor for larger ones.
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It is more complex and powerful requiring more resoureces to manage.
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It is simpler and easier to manage than RDBMS.
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RDBMS (Relational Database Management System) provides a number of advantages over file-based systems namely :
- Data integrity: Data integrity is enforced by RDBMS. The data is stored in a consistent and accurate manner by using constraints such as primary keys, foreign keys, and data types.
- Data security: A variety of security features are provided here to protect the data from unauthorized access, modification, or deletion. The mentioned features include authentication, authorization, and encryption.
- Data concurrency: Besides allowing multiple users to access and modify data simultaneously it does not cause conflicts. All this is done by using locking mechanisms, ensuring only one user can modify a piece of data at a time.
- Data scalability: These databases are designed to scale to large amounts of data. Thus can be easily scaled up or down to meet the needs of any application.
- Data flexibility: RDBMS can be used to store a huge variety of data types making it flexible for it’s users also idealising it for a wide range of applications.
Advantages of File Based over RDBMS System
File based storage systems have numerous advantages over RDBMS systems. They are as follows ;
- Simplicity: File-based systems follow a hierarchichal structure making them simpler to set up and manage than RDBMS systems. Thus they do not require any special software or expertise to use.
- Portability: File-based system(s) is more portable than RDBMS system as data here can be easily transferred between different computers and operating systems.
- Performance: File-based systems can provide overall better performance for small to medium-sized datasets.
- Cost: A file-based system is less expensive to purchase and maintain than the RDBMS system.
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