This semester in my computer-assisted reporting class, we’re giving a new database manager a look: SQLite Manager. The program is an add-on for Mozilla Firefox browsers and takes just a few seconds to install. Users work with self-contained SQLite database files, which have a .sqlite extension.
SQLite touts itself as the “most widely used and deployed” database engine, running on every Android phone and iOS device and inside many popular web browsers.
Before, we used MySQL Community Server and Navicat Essentials client for MySQL, whose installation sometimes consumed an entire 75-minute class, depending on the snags students encountered. An unfortunate few students running Macs were beset by fatal errors that sent them scrambling for tech support outside class.
So, what a relief to set up a database manager in a fraction of the time that it took before.
However, there is a learning curve in switching from other database managers, such as MySQL and Microsoft Access. We’ve discovered some pretty significant differences in how SQLite behaves.
First, SQLite is case sensitive when evaluating WHERE statements for text. For instance, the following statement will only find variations of Columbia that are spelled in proper case. It will miss columbia or COLUMBIA.
WHERE city = "Columbia"
To pick up the other variations, we would need to rewrite WHERE to:
WHERE city = "Columbia" OR city = "columbia" OR city = "COLUMBIA"
WHERE city IN("Columbia", "columbia", "COLUMBIA")
In the alternative, we could use LIKE to pick up the variations. LIKE is case sensitive by default, but that can toggled off by running the following PRAGMA statement in the SQL editor:
PRAGMA case_sensitive_like = false
Now we can run the following SQL to pick the three different ways Columbia is stored:
WHERE city LIKE “columbia”
As someone who’s primarily a MySQL user, this struck me as odd. In MySQL and Access we usually use LIKE in concert with wildcard characters to match parts of text inside a field. That allows us to get any city field entries like this: Columbia, Mo.
In SQLite, we can do that, too, with this statement:
WHERE city LIKE "columbia%"
The % symbol in SQLite is the wildcard for any number of characters. So we would get all records where the city starts with columbia and ends with anything.
The other wildcard is the underscore ( _ ) and stands for exactly one character.
A couple of other SQLite quirks:
- There’s no way to store things that look like dates in date-formatted fields. Unlike MySQL and Access, SQLite lacks a date data type. (Check out item 1.2). However, we can use date and time functions to work with date information that’s stored as text in this manner: yyyy-mm-dd.
- The program runs queries where the SELECT and GROUP BY statements are out of whack. Most of the time, these queries will generate inaccurate results that may look OK. Access will not do that and instead throws an error message. MySQL will run those queries, but it does give us the option to change the program to full GROUP BY mode by issuing a SQL command.