When working with databases that are not properly designed/normalized, we could encounter different anomalies that could affect the integrity of the database.
Database anomalies refer to inconsistencies or errors that can occur within a relational database during data insertion, deletion, or modification. These anomalies can lead to unexpected behaviors and data integrity issues.
Here are the different types of database anomalies:
1. INSERT/INSERTION ANOMALY
- An insert anomaly is a situation in a relational database where inserting new data into a table leads to undesirable effects, such as the inability to insert a record due to missing attribute values or the duplication of data
2. UPDATE ANOMALY
- An update anomaly occurs when modifying data in a database leads to inconsistencies. When updating data, we expect the changes to be consistent across related records. An update anomaly arises when only part of the data is updated, leaving other related instances unchanged. This results in conflicting or contradictory information within the database.
3. DELETE ANOMALY
- A delete anomaly is a situation in a relational database where deleting a record (tuple) from a table unintentionally results in the loss of other related data
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