Case sensitivity in Sql Server depends on the collation applicable to the column, which of course is often the same as the database default collation. Unlike Oracle, Sql Server out of the box is case-insensitive (at least in English-speaking Western countries).
This means that you don’t need to consider whether data is upper- or lower-case when you’re searching for it, which tends to make an application more robust. You probably won’t want to change that. On the other hand, if your database stores codes or descriptions used as query filters (not including proper nouns like personal names where the capitalisation is part of the data) there may be an advantage to standardising on upper or lower case. You’ve reduced the need to take account of upper/lower case in client code, where string comparisons may be case-sensitive.
Is there an easy way? Yes. Continue reading
The JSON has landed (in beta at least) – and I think it’s now some practical use. I’ve collected a few technical references here. There may not be a native JSON type yet, but there are workarounds to provide the kind of assurance control-freak RDBMS developers find comforting. I’ve shown some of them in the code sample below. Continue reading
Some hand-matching of internal/external records may be needed even in an automated reconciliation. The matches will be stored in a database. Rules on matching can be enforced in the application, but there are often good reasons to place them in the database. In Sql Server, a filtered index (with a WHERE clause, in this case excluding Nulls) on the table can make this easier and more correct. Continue reading
Indexes often double as constraints. Each combination of values must only appear once among the columns of an index defined as UNIQUE. The “filtered” index allows some refinement. Suppose that in one column you won’t allow a specific value to appear more than once, but you don’t mind other values being duplicated.
A good example would be the IS_LATEST_VERSION column in a data warehouse table. Continue reading
Well, not literally – these are features I tend to overlook because I don’t often need them. If you’re the same, this may be helpful. It isn’t a complete list (I’ve forgotten the others) but I’ll try to add to it as things come to mind. Continue reading
“Stretching” the database now means migrating some or all data from local database tables into the Azure Cloud. The result is a hybrid design: each local table then has a counterpart in the cloud. Any query against the local table will be transparently re-written to include data from the “cloud table”. Continue reading
A phase of my Agile Blue/Green deployment project is now complete, as I have a Proof of Concept which has been tested successfully. As you may recall from prior posts, the Blue/Green technique features two databases, the “green” live one that users connect to (I’ve made an arbitrary assignment of colours), and the offline “blue” one which has a different version of the schema (a previous or future release). Continue reading