If there’s one thing that SQL Server is really good at, it’s relationships. After all, a relational database management system without the relationships is nothing more than a place to store your stuff. Last week we briefly looked at a denormalized table, and then I suggested that breaking it up into five separate tables would[…]
Phew! There’s a lot to take in with data types, collation, precision, scale, length, and Unicode, and we’re just getting warmed up. This week’s post is over 2,000 words long!
Over the last three weeks, we’ve gone fairly deep into data types, and now we are going to see how they come into play with normalization.
If we go back to the first post in this series, I mentioned normalization, and then apparently I forgot about it in the next two posts. What you didn’t see is that I was talking about it all along.
Last week, we discussed storing text in a database. This week we will dive deeper into data types. When storing data in our database, we want to make sure that it’s stored accurately and that we only use the required amount of space. This is because when we access the data later, we want to[…]
This is part two of a short series of posts about how I assign efficient data types when designing a new table or database. Use less space with BIGINT Last week, I spoke about a more efficient DATETIME than DATETIME. This week I have a more efficient DECIMAL than DECIMAL. If you’re planning to store[…]
This is the first in a short series of posts about how I assign efficient data types when designing a new table or database. Use less space with DATETIME2 We all know that the DATETIME column uses 8 bytes of space to store the date and time, to an accuracy of a paltry 3 milliseconds. This[…]