A normalized design will often store different but related pieces of information in separate logical tables (called relations). If these relations are stored physically as separate disk files, completing a database query that draws information from several relations (a join operation) can be slow. If many relations are joined, it may be prohibitively slow. There are two strategies for dealing with this. The preferred method is to keep the logical design normalized, but allow the DBMS to store additional redundant information on disk to optimize query response. In this case it is the DBMS software's responsibility to ensure that any redundant copies are kept consistent. This method is often implemented in SQL as indexed views. A view represents information in a format convenient for querying, and the index ensures that queries against the view are optimized.
The more usual approach is to denormalize the logical data design. With care this can achieve a similar improvement in query response, but at a cost—it is now the database designer's responsibility to ensure that the denormalized database does not become inconsistent. This is done by creating rules in the database called constraints, that specify how the redundant copies of information must be kept synchronized. It is the increase in logical complexity of the database design and the added complexity of the additional constraints that make this approach hazardous.
Examples of a denormalization techniques include: