Advantages and Disadvantages of RDBMS
RDBMS is one of the most widely used methods for data storage. Because it has certain advantages and some drawbacks that make it difficult to use, it is always helpful in keeping records of the connections between various things. A relational database is a technology that helps organizations store and manage their information in a structured way. It was developed in the late 1970s and has been widely used. These databases are crucial tools that enable corporations to store and manage their data effectively,
Relational Database Management Systems (RDBMS) and SQL databases are also used to refer to relational databases. They are the kind of database that businesses use the most frequently. IBM DB2, Oracle, Microsoft SQL Server, and MySQL were the most well-liked. The majority of the time, large enterprises use relational databases. These are essential for organizations because they provide the ability to store, retrieve, manage, and modify data while providing a direct line to the many departments that require it.
Relational databases connect tables to reveal relationships, while non-relational databases group related documents in flexible formats. Each type has its advantages based on specific requirements.
Users of Relational Database
1) Database administrators: They are responsible for keeping the system's maintenance current and tracking performance. Along with other system-related concerns, they are responsible for maintaining the database's security and consistency.
2) Software Developers: The database is created and designed by developers and coders. Languages used for programming allow programmers to communicate with the database.
3) End-User: This person can input, edit, and remove data and execute the task of retrieving data and information within the system using commands.
Advantages of RDBMS
Following are the eight advantages of relational database management systems:
1) Data Integrity: RDBMS establishes limitations on data, including primary keys, unique keys, and referential integrity. This assures that the data is accurate and reliable.
2) Compatibility for Structured Query Language (SQL): A standard language (SQL) is provided by RDBMS to allow data querying and manipulation. SQL is extensively used and makes working with the database simple.
3) Scalability: RDBMS may grow horizontally by clustering or vertically by adding more robust hardware. It can also manage massive volumes of data. This enables meeting increasing data demands.
4) Consistency: RDBMS uses the ACID qualities (Atomicity, Consistency, Isolation, Durability) in transactions to maintain data consistency. This ensures that data maintains its integrity even when concurrent activities occur.
5) Data Security: To protect sensitive data from unauthorized access or alteration, RDBMS provides robust security features, including user authentication, access control, and encryption.
6) Data Independence: RDBMS offers data separation between the logical schema and physical storage. Without impacting the database apps, this division makes maintenance and updates easier.
7) Data Sharing and Concurrency Control: RDBMS permits concurrent usage of the database by numerous users. It protects data integrity through locking methods and transaction isolation while allowing concurrent operations on shared data.
8) Compliance with Standards: RDBMS complies with ANSI/ISO standards, enabling system and platform compatibility and interoperability. This makes system integration and data interchange easier.
Disadvantages of RDBMS
Following are the four disadvantages of relational database management systems:
1) Limitations on Scalability: RDBMS may need scaling when dealing with huge data volumes or high-speed data processing demands. Passing a specific point on the scale might be difficult.
2) Performance Overhead: Because of the cost associated with maintaining relationships, enforcing constraints, and running complicated queries, RDBMS can cause performance excess. The response time and efficiency of the system may be affected.
3) Fixed Schema: In a relational database, how the data is organized and related to each other is predetermined and cannot be easily changed. This means that any database structure can easily adapt the modifications, such as adding new fields or changing relationships between tables.
4) High Cost of Ownership: The implementation and maintenance of RDBMS might be expensive. It covers licensing fees, hardware costs, and the expense of hiring qualified staff for management, performance tuning, awnd optimization.
5) Lack of Flexibility: RDBMS may need help to handle hierarchical data, documents, or other unstructured or semi-structured data types, such as those found in photos or documents. There might be better options for some use cases or data structures.
6) Single Point of Failures: Whenever the database server fails, or crashes, RDBMS could become a single point of failure. If proper backup and recovery procedures aren't in place, this might result in interruptions and information loss.
7) The experience curve: RDBMSs can have a high learning curve, particularly for complicated activities like query optimization, database management, and performance tuning. Much work may be necessary to become skilled in these fields.
8) Not Fit for Real-time Data Processing: Specialised systems like stream processing engines may be more effective for real-time or rapid data processing applications with low latency and real-time analytics.