What is Denormalization in Relational Database Management System?

Concept: Normalization organizes a relational schema to eliminate redundant data and keep every fact stored in exactly one place, which protects data integrity but forces read queries to join many small tables together. Denormalization is the deliberate reverse of that trade-off: it reintroduces controlled redundancy — duplicating columns, merging related tables, or precomputing derived values — so that read-heavy queries can retrieve data with fewer joins, at the cost of some update overhead and storage.

Application: For this question, denormalization is defined precisely as the process of increasing redundancy in a schema in order to improve (read) performance. A database administrator applies it after the schema has already been normalized, when query speed on large, read-heavy tables becomes the priority over strict non-redundancy.

• Decreasing redundancy in a database is what normalization achieves, not denormalization — the two techniques pull the schema in opposite directions.

• Decreasing dependence on normal forms is not what denormalization is measured by; its scope is redundancy and join cost, not a count of dependency rules.

• Developing a new schema describes schema design from scratch, whereas denormalization only reshapes an existing, already-normalized schema for performance.

Cross-check: Standard database references (IBM Db2, Oracle documentation) define denormalization the same way — as intentionally adding redundancy to a normalized schema to speed up retrieval — confirming that increasing redundancy for performance is the accurate definition among the options offered.