Logical Database Design

Optimizing SQL Database Performance

Optimizing Database Performance

Logical Database Design

Using Microsoft® SQL Server™ 2000 effectively begins with normalized database design. Normalization is the process of removing redundancies from the data. For example, when you convert from an indexed sequence access method (ISAM) style application, normalization often involves breaking data in a single file into two or more logical tables in a relational database. Transact-SQL queries then recombine the table data by using relational join operations. By avoiding the need to update the same data in multiple places, normalization improves the efficiency of an application and reduces the opportunities for introducing errors due to inconsistent data.

However, there are tradeoffs to normalization. A database that is used primarily for decision support (as opposed to update-intensive transaction processing) may not have redundant updates and may be more understandable and efficient for queries if the design is not fully normalized. Nevertheless, data that is not normalized is a more common design problem in database applications than over-normalized data. Starting with a normalized design, and then selectively denormalizing tables for specific reasons, is a good strategy.

For more information, see Normalization.

Whatever the database design, you should take advantage of these features in SQL Server to automatically maintain the integrity of your data:

  • CHECK constraints ensure that column values are valid.

  • DEFAULT and NOT NULL constraints avoid the complexities (and opportunities for hidden application bugs) caused by missing column values.

  • PRIMARY KEY and UNIQUE constraints enforce the uniqueness of rows (and implicitly create an index to do so).

  • FOREIGN KEY constraints ensure that rows in dependent tables always have a matching master record.

  • IDENTITY columns efficiently generate unique row identifiers.

  • timestamp columns ensure efficient concurrency checking between multiple-user updates.

  • User-defined data types ensure consistency of column definitions across the database.

By taking advantage of these features, you can make the data rules visible to all users of the database, rather than hiding them in application logic. These server-enforced rules help avoid errors in the data that can arise from incomplete enforcement of integrity rules by the application itself. Using these facilities also ensures that data integrity is enforced as efficiently as possible.

See Also

Data Integrity