Every database covered in the article is a toy.
"The problem is that JOINs are really, really slow when the data is spread out over several machines."
This is the result of a poor design, not a database flaw. If you are running a web application against multiple databases, either cluster them or store all the data for a user in one database. (i.e. hash the login_id and select the database based on the result). If someone is doing JOINs across multiple machines and doesn't have a very good reason for doing so, then nothing short of a lobotomy is going to help them.
"Each query can only run 5 seconds. The answer can only hold 250 items. Each item can have only 250 pairs."
Yeah, I'd say that meets the definition of a toy database alright.
"Many of the complaints about the other toy databases revolve around how a missing feature makes it impossible to find the right data. If you want to add a bit more functionality to the database here, you can whip up many of the features locally in Python. If you want a JOIN, you can synthesize one in Python and probably customize the memory cache at the same time. This is especially useful for Web applications that let users store their data in the service. If you need to add security to restrict each user to the right data, you can code that in Python too."
The writer must be joking. Who would do this when there are better options that don't involve implementing your own database?
Many people who write web applications actually want to do usefull things with the data they store like generate reports, keep logs, track inventory, or run queries. This doesn't work very well when the "database" is a text file sitting on the user's harddrive.