What is the difference between 3NF and BCNF in database management system? The former focus is on eliminating transitive dependencies while the latter on eliminating non-trivial functional dependencies where the determinant is not a superkey.
Both 3NF (Third Normal Form) and BCNF (Boyce-Codd Normal Form) are stages of normalization in database management systems, and they are designed to eliminate certain types of data anomalies and redundancies.
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Difference between 3NF and BCNF in Database Management System (With Table)
Basic Terms | 3NF | BCNF |
Dependency Handling | Focuses on eliminating transitive dependencies. | Focuses on eliminating non-trivial functional dependencies where the determinant is not a superkey. |
Stringency | Less stringent compared to BCNF. | More stringent compared to 3NF. Every determinant of a non-trivial functional dependency must be a superkey. |
Candidate Keys | No specific requirement regarding superkeys for functional dependencies. | Every determinant of a non-trivial functional dependency must be a superkey. |
Purpose | Designed to reduce data redundancy and eliminate transitive dependencies. | Aims to achieve further normalization by addressing additional constraints related to functional dependencies. |
Normal Form Level | Follows 2NF and aims to eliminate transitive dependencies. | Follows 3NF and ensures additional constraints regarding functional dependencies. |
Dependency Types | Focuses on eliminating transitive dependencies among attributes. | Focuses on ensuring that non-trivial functional dependencies are based on superkeys. |
Applicability | Commonly used and sufficient for many database designs. | Useful in more advanced scenarios where stricter normalization is required. |
Table Example | For example, consider a table with attributes A, B, and C, where A -> B and B -> C. | For example, consider a table with attributes A, B, and C, where A -> B and B -> C. In BCNF, A must be a superkey. |
Normalization Level | A lower level of normalization compared to BCNF. | A higher level of normalization compared to 3NF. |
Redundancy | Reduces redundancy by eliminating transitive dependencies. | Further reduces redundancy by addressing non-trivial functional dependencies. |
What Is 3NF in Database Management System?
Third Normal Form (3NF) is a stage in the normalization process of a relational database schema. Normalization is a technique used to organize the data in a database to reduce redundancy and dependency. The primary goal of 3NF is to eliminate transitive dependencies.
A table is said to be in 3NF if it satisfies the following conditions:
First Normal Form (1NF): The table must be in 1NF, which means that it should have a primary key, and all its columns must contain atomic (indivisible) values.
Second Normal Form (2NF): The table must be in 2NF, meaning that it should be in 1NF and there should be no partial dependencies. In other words, all non-prime attributes (attributes not part of any candidate key) must be fully functionally dependent on the primary key.
Elimination of Transitive Dependencies: The table should not have any transitive dependencies. A transitive dependency occurs when a non-prime attribute depends on another non-prime attribute, which, in turn, depends on the primary key.
To eliminate transitive dependencies, you break the table into two tables, where the dependent attributes are moved to another table along with their determinant.
What Is BCNF in Database Management System
Boyce-Codd Normal Form (BCNF) is a higher level of normalization in database management systems, building upon the concepts of 1NF, 2NF, and 3NF. BCNF is designed to further eliminate certain types of anomalies and ensure that a relational database schema is free from certain kinds of redundancies. It was developed by Raymond F. Boyce and Edgar F. Codd.
A table is said to be in BCNF if it satisfies the following conditions:
It is in 1NF, 2NF, and 3NF: Before a table can be in BCNF, it must already meet the requirements of the first three normal forms.
Functional Dependency Criterion: For every non-trivial functional dependency (X -> Y), where X is a set of attributes and Y is an attribute, X must be a superkey. This means that every determinant (X) should be a candidate key.
The BCNF condition addresses cases where a non-prime attribute is functionally dependent on another non-prime attribute, and both are not part of any candidate key.
By enforcing the BCNF condition, we ensure that there are no redundant dependencies and that the table structure is free from certain types of anomalies.
Main Difference between 3NF and BCNF in Database Management System
Dependency Handling
- 3NF eliminates transitive dependencies.
- BCNF eliminates non-trivial functional dependencies where the determinant is not a superkey.
Stringency
- 3NF is less stringent compared to BCNF.
- BCNF is more stringent than 3NF.
Candidate Keys
- 3NF has no specific requirement regarding superkeys for functional dependencies.
- BCNF requires every determinant of a non-trivial functional dependency to be a superkey.
Applicability
- 3NF is commonly used and sufficient for many database designs.
- BCNF is useful in more advanced scenarios where stricter normalization is required.
Similarities between 3NF and BCNF in Database Management System
- Both require a table to be in 1NF and 2NF before applying their specific conditions.
- Both are stages of normalization in relational database design.
- Both aim to reduce redundancy and eliminate certain types of data anomalies.
- Both address issues related to functional dependencies in a relational database schema.
Conclusion
The distinction between 3NF and BCNF lies in their specific approaches to normalization in a relational database. While 3NF primarily focuses on the elimination of transitive dependencies, BCNF takes a more stringent stance by addressing non-trivial functional dependencies and requiring that every determinant be a superkey.
Both serve the common goal of reducing redundancy and ensuring a well-structured database, with 3NF being more widely applicable, and BCNF being reserved for scenarios demanding a higher level of normalization.
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