Armstrong’s Axiom

Definition of Armstrong’s Axiom

Armstrong’s Axioms are a set of inference rules used in relational database theory to infer functional dependencies based on a set of given dependencies. They were introduced by William W. Armstrong in 1974 and provide a logical foundation for the normalization of database schemas. The three axioms are reflexivity, augmentation, and transitivity.


Armstrong’s Axiom in phonetics is: /ˈɑrmstrɒŋz ˈæksiəm/

Key Takeaways

  1. Armstrong’s Axioms are a set of rules used to infer all the functional dependencies in a relation schema of a database, which is crucial for data normalization and the reduction of redundancy.
  2. These axioms consist of three inference rules – Reflexivity, Augmentation, and Transitivity – that can be applied iteratively to generate a complete set of functional dependencies in a database schema.
  3. Armstrong’s Axioms are sound and complete, meaning that they yield only true functional dependencies and can be used to derive all true functional dependencies present in the schema.

Importance of Armstrong’s Axiom

Armstrong’s Axiom is an essential concept in database theory, particularly in the context of functional dependencies and normalization.

Named after William W.

Armstrong, these axioms, comprising of reflexivity, augmentation, and transitivity, serve as a foundation for inferring all possible functional dependencies, which dictate the relationships between attributes in a relational database schema.

Ensuring that these dependencies follow Armstrong’s Axioms helps maintain database consistency, prevent data redundancy, and optimize query performance.

By adhering to these principles, database designers can create normalized and efficient database structures, ultimately enhancing the quality and reliability of the systems that depend on them.


Armstrong’s Axiom, a fundamental concept in the field of database management, primarily serves the purpose of establishing essential guidelines for maintaining data integrity, consistency, and accuracy in relational databases. Developed by William W.

Armstrong in the mid-1970s, it comprises of a set of rules, or axioms, that facilitate the reasoning about, and derivation of functional dependencies among attributes within a relational data model. By ensuring that functional dependencies are correctly identified and addressed, Armstrong’s Axiom enforces the normalization of database schemas, preventing redundant information and data anomalies from arising.

In practical applications, Armstrong’s Axiom is utilized by database administrators and developers to design and optimize relational database schema. This is achieved by decomposing tables containing problematic data relationships into multiple tables with well-defined functional dependencies and minimal redundancy.

The axiom forms the foundation of the normalization process, guiding schema design decisions that minimize common issues such as data inconsistency, update anomalies, and inefficiencies in data storage. In summary, Armstrong’s Axiom is crucial to ensuring the quality, efficiency, and reliability of relational database systems by enabling proper management of data dependencies.

Examples of Armstrong’s Axiom

Armstrong’s Axiom, also known as Armstrong’s Axioms, is a foundational concept in the field of database management, specifically in the area of database schema design and normalization. Armstrong’s Axioms provide a set of rules for determining functional dependencies between attributes in a relation, which help in designing a well-structured database.Here are three real-world examples of how Armstrong’s Axioms could be applied:

E-commerce store: In an e-commerce store’s database, product details like product_id, product_name, and product_category are related. Using Armstrong’s Axioms, designers can determine the functional dependencies to create an efficient schema that avoids redundant information. In this case, product_id → product_name and product_id → product_category are functional dependencies, ensuring that every product_id corresponds to only one product_name and product_category.

Student management system: Educational institutions often have databases to manage student information. The database may contain attributes like student_id, student_name, course_id, course_name, and instructor. Armstrong’s Axioms can be used to identify functional dependencies, such as student_id → student_name, course_id → course_name, and course_id → instructor. This information can be further used to normalize the database and reduce data redundancy.

Hospital patient records: In a hospital’s patient record management system, attributes may include patient_id, patient_name, doctor_id, doctor_name, and department. By applying Armstrong’s Axioms to these attributes, functional dependencies like patient_id → patient_name, doctor_id → doctor_name, and doctor_id → department can be found. Identifying these dependencies aids in designing a more efficient and normalized database schema, reducing data redundancy and ensuring data integrity.

Armstrong’s Axiom FAQ

What is Armstrong’s Axiom?

Armstrong’s Axiom is a set of inference rules used to reason about functional dependencies in a relational database schema. These axioms, proposed by William W. Armstrong, provide a formal foundation for understanding the relationships between attributes in a database and facilitate the process of normalization.

What are the three rules of Armstrong’s Axiom?

The three rules of Armstrong’s Axiom are reflexivity, augmentation, and transitivity.

What is the reflexivity rule?

The reflexivity rule states that if a set of attributes B is a subset of a set of attributes A, then A functionally determines B. In other words, if all attributes in B are also in A, then the functional dependency A → B holds true.

What is the augmentation rule?

The augmentation rule states that if A → B, and C is any set of attributes, then AC → BC. This means that if A functionally determines B, adding any attributes to both A and B does not change the functional dependency.

What is the transitivity rule?

The transitivity rule states that if A → B and B → C, then A → C. In other words, if A functionally determines B, and B functionally determines C, then it follows that A functionally determines C.

How are Armstrong’s Axioms used in database design?

Armstrong’s Axioms are used in the process of database normalization to identify and eliminate redundancy and potential anomalies. By reasoning about functional dependencies and ensuring compliance with the axioms, database designers can create well-structured and efficient database schemas.

Related Technology Terms

  • Functional Dependencies
  • Normalization in Database
  • Relational Algebra
  • Database Optimization
  • Canonical Cover

Sources for More Information


About The Authors

The DevX Technology Glossary is reviewed by technology experts and writers from our community. Terms and definitions continue to go under updates to stay relevant and up-to-date. These experts help us maintain the almost 10,000+ technology terms on DevX. Our reviewers have a strong technical background in software development, engineering, and startup businesses. They are experts with real-world experience working in the tech industry and academia.

See our full expert review panel.

These experts include:


About Our Editorial Process

At DevX, we’re dedicated to tech entrepreneurship. Our team closely follows industry shifts, new products, AI breakthroughs, technology trends, and funding announcements. Articles undergo thorough editing to ensure accuracy and clarity, reflecting DevX’s style and supporting entrepreneurs in the tech sphere.

See our full editorial policy.

More Technology Terms

Technology Glossary

Table of Contents