Databases: Denormalisation
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Denormalization involves deliberately relaxing normalization rules to introduce redundancy into a database design in order to improve performance when a fully normalized system is unable to meet performance requirements. It may involve combining relations so they remain normalized but contain null values, or leaving relations in second normal form instead of moving to third normal form. While denormalization can speed up retrievals, it often sacrifices flexibility and slows down updates, making implementation more complex. Normalization is still important, but denormalization may be used after considering performance needs versus these tradeoffs.
Databases: Denormalisation
- 2. Question ? The result of normalisation is a logical database design that is structurally consistent and has minimal redundancy.
- 3. Question ? Does it ever make sense to deliberately relax normalisation rules and deliberately introduce redundancy into the system.
- 4. Denormalisation The answer is yes, but only when it is estimated that the system may not be able to meet its performance requirements.
- 5. Denormalisation A fully normalised system does not necessarily provide maximum processing efficiency. In this situation introducing redundancy in a controlled manner by relaxing the normalisation rules will improve the performance of the system.
- 6. Denormalisation When we talk about denormalisation we are not just talking about degrees and forms. For example, we may decide to have some portion of the logical data model in 2NF and the rest in 3NF.
- 7. Denormalisation In general we are loosely using the term to refer to situations where we combine relations and the new relation is still normalised but may contain nulls.
- 8. Denormalisation Consider the earlier example we did. We produced a new Relation Owner when we went from 2NF to 3NF. Now when we look up a property for rent we need to access two tables instead of one. In some situations we may decide to leave the relations in 2NF.
- 9. Denormalisation Normalisation is still very important for database design. In addition the following factors have to be considered: Denormalisation makes implementation more complex. Denormalisation often sacrifices flexibility Denormalisation may speed up retrievals but it slows down updates.