RDBMS stands for Relational Database Management Systems. A database is an organized collection of data stored in a computer system and usually controlled by a database management system (DBMS). The data in common databases is modeled in tables, making querying and processing efficient.
What is RDBMS?
Relational Database Management Systems are referred to as RDBMS. A relational database can be created, deleted, and updated with this tool. A relational database is a type of database system that uses rows and columns to organize and store data in a tabular fashion. It is a more compact version of DBMS, which was created in the 1970s by E.F. Codd. Relational DBMS concepts are the foundation of the main DBMSs, including SQL, My-SQL, and Oracle.
The core of relational database management systems is the relationship between each table’s values. Larger data sets can be handled by it, and it can readily mimic queries.
Relational database management systems mimic the following characteristics to preserve data integrity:
- Entity Integrity: No two records of the database table can be completely duplicate.
- Referential Integrity: Only the rows of those tables can be deleted which are not used by other tables. Otherwise, it may lead to data inconsistency.
- User-defined Integrity: Rules defined by the users based on confidentiality and access.
- Domain integrity: The columns of the database tables are enclosed within some structured limits, based on default values, type of data or ranges.
RDBMS History
E. F. Codd’s work at IBM in the 1970s marked the beginning of the history of relational database management systems, or RDBMS. In 1970, Codd presented the idea of relational databases, which employ SQL (Structured Query Language) to query data. This model’s emphasis on data integrity and reduction of redundancy transformed data management. During the 1980s, relational databases became the industry standard for data management when commercial RDBMS solutions like Oracle, IBM DB2, and Microsoft SQL Server appeared. RDBMS technology has developed further over the years, integrating improvements in performance, scalability, and support for sophisticated queries, solidifying its position as a fundamental component of contemporary database administration.
What is a Database Table?
A table is a collection of related data in an organized manner in the form of rows and columns. It is an organized arrangement of data and information in tabular form containing rows and columns, making it easier to understand and compare data. Here is the pictorial representation of the table and its different components containing the data about different students that is ID, name, Age, and course.
Features of RDBMS
- In a database file, the data must be tabular, meaning it must be arranged in rows and columns.
- Every table row is referred to as a record or tuple. The cardinality of the table is the collection of such records.
- Every table column is referred to as an attribute or field. The table’s arity is a collection of these columns.
- The DB table’s records cannot be identical. Thus, employing a candidate key prevents data duplication. The bare minimum of characteristics needed to uniquely identify each record is known as the candidate key.
- Foreign keys are used to relate tables to one another.
- Database tables also allow NULL values, that is if the values of any of the element of the table are not filled or are missing, it becomes a NULL value, which is not equivalent to zero. (NOTE: Primary key cannot have a NULL value).
Uses of RDBMS
- The field of customer relationship management uses RDBMS.
- Online retail platforms use it.
- In hospital management systems, it is utilized.
- Business intelligence uses it.
- The use of it is in data warehousing.
SQL Query in RDBMS
Creating a Table
Syntax:
CREATE TABLE table_name (
column1_name datatype constraint,
column2_name datatype constraint,
);
Example:
CREATE TABLE Employees (
EmployeeID INT PRIMARY KEY,
FirstName VARCHAR(50),
LastName VARCHAR(50),
BirthDate DATE,
Salary DECIMAL(10, 2)
);
2. Inserting Data into a Table
Syntax:
INSERT INTO table_name (column1_name, column2_name, …)
VALUES (value1, value2, …);
Example:
INSERT INTO Employees (EmployeeID, FirstName, LastName, BirthDate, Salary)
VALUES (1, ‘John’, ‘Doe’, ‘1985-06-15’, 55000.00);
3. Querying Data (SELECT)
Syntax:
SELECT column1_name, column2_name, …
FROM table_name
WHERE condition;
Example:
SELECT FirstName, LastName, Salary
FROM Employees
WHERE Salary > 50000;
4. Deleting Data from a Table
Syntax:
DELETE FROM table_name
WHERE condition;
Example:
DELETE FROM Employees
WHERE EmployeeID = 1;
5. . Dropping a Table
Syntax:
DROP TABLE table_name;
Example:
DROP TABLE Employees;
Advantages of RDBMS
- Simple to Manage: You can change any table on your own without affecting the others.
- Security: With several security tiers, it is more secure. Access to shared data may be restricted.
- Flexible: Data can be updated at one location without requiring changes to several files. More records may be added to databases with ease, increasing their scalability. Additionally, it makes using SQL queries simple.
- Users: Multiple users can be stored together using the client-side architecture supported by RDBMS.
- makes it easier to store and retrieve vast amounts of data.
- Simple Data Management:
- Relational architecture makes data retrieval faster.
- Keys, indexes, and normalization principles prevent data redundancy or duplication.
- Since RDBMS is predicated on ACID qualities for data transactions, data consistency is guaranteed.
- Data fetching is faster because of relational architecture.
- Data redundancy or duplicity is avoided due to keys, indexes, and normalization principles.
- Data consistency is ensured because RDBMS is based on ACID properties for data transactions(Atomicity Consistency Isolation Durability).
- Fault Tolerance: Replication of databases provides simultaneous access and helps the system recover in case of disasters, such as power failures or sudden shutdowns.
Disadvantages of RDBMS
- High Cost and Extensive Hardware and Software Support: These systems demand significant setups and costs in order to operate.
- Scalability: More servers, more power, and more memory are needed when more data is added.
- Complexity: Large amounts of data make it harder to understand relationships and can impair performance.
- Structured restrictions: A relational database system’s fields and columns are surrounded by a number of restrictions that could cause data loss.
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