UpdateAnomalien

UpdateAnomalien, commonly referred to as update anomalies, describe inconsistencies that can occur in a database when data is redundantly stored and modification operations are performed on tables that are not normalized properly. They arise during insert, update, or delete operations and can lead to inconsistent data across rows or related records.

There are three classic forms: insertion anomalies, update anomalies, and deletion anomalies. An insertion anomaly occurs when certain information cannot be added without including other data due to missing related data. An update anomaly happens when changing a value in one row requires updating multiple rows to maintain consistency, and some rows may be overlooked. A deletion anomaly occurs when removing data unintentionally erases information that should remain because related data is stored together in a way that depends on other records.

A common illustration involves a single table that stores both product information and supplier details. If product price or availability is tied to a supplier, updating one attribute may require changes across multiple rows, and removing a supplier could delete products that are still relevant. These scenarios illustrate how redundancy and dependency issues can propagate inconsistent state.

Normalization is the primary approach to mitigate update anomalies. By splitting data into related tables and enforcing keys and constraints, redundancy is reduced and updates are localized. Achieving at least third normal form (3NF) or Boyce-Codd normal form (BCNF) helps prevent anomalies. In practice, some systems adopt controlled denormalization for performance, but this reintroduces the risk of anomalies if integrity constraints and transactions are not carefully managed.

Related concepts include functional dependency, database normalization, foreign keys, and ACID transactions. UpdateAnomalien are a key consideration in designing robust, consistent relational schemas.