"I actually started out writing an article on how to pass 1, 2, and 3 dimensional "arrays" as parameters in stored procedures. Suddenly it dawned on me that a lot of people still have no clue what a "numbers" or "Tally" table is, never mind how it actually works."
"SQL Server 2008 introduces two tracking features that enable applications to determine the DML changes (insert, update, and delete operations) that were made to user tables in a database. Before these features were available, custom tracking mechanisms had to be implemented in applications. These custom mechanisms often required schema changes to the tracked table or the use of triggers. Neither change data capture nor change tracking requires any schema changes at the source or the use of triggers."
"There can be a great difference in the performance of a particular routine in a test database, and in a fully loaded production system. When you hit performance problems in a database under load, and there is excessive locking and blocking, how can you determine exactly where the problems lie, in order to fix them? Read on..."
"Returns information from, or expressions based on, each row affected by an INSERT, UPDATE, DELETE, or MERGE statement. These results can be returned to the processing application for use in such things as confirmation messages, archiving, and other such application requirements. The results can also be inserted into a table or table variable. Additionally, you can capture the results of an OUTPUT clause in a nested INSERT, UPDATE, DELETE, or MERGE statement, and insert those results into a target table or view."
Hammock is a .NET CouchDB library modeled directly on NHibernate and strives for much of the same functionality while avoiding the vast complexity of mapping object data to a relational system.
"Column-Based Query Accelerator will help dramatically increase query performance ~10x and reduce performance tuning through interactive experiences with data for near instant response times and streamlined setup which removes the need to build summary aggregates."
"Recently I encountered a case when I knew much more about the data than the optimizer. Originally the performance was horrible, this is why I had to have a look at the query in the first place. When I was able to share my knowledge with the optimizer, it produced a better plan, and the query ran dramatically faster."