The beauty of cloud solutions like AppEngine and its database, called Datastore: it just scales. It does indeed scale very well, but it does so by applying a few restrictions. In the case of Datastore that is "eventual consistency", something you're not used to when you're used to conventional databases like MySQL.
What does eventual consistency mean?Here's a really simple example to describe it: You have a table called Messages where you store messages sent by the users of your website (a chatroom, or guestbook, etc). When the page is reloaded you query all data from the Messages-table and display it. Someone enters a message and it's stored in the database. The page is reloaded moments later and all Messages are looked up using a query. The recently stored message does not show up though. Because eventual consistency!
After changing (creating, updating, deleting) data in your database, queries executed moments later might (!) not return the latest data in some cases. Eventually, though, it is going to return those changes. It might be nanoseconds, seconds, ... later.
Your first thought might be that this is awful, however it isn't. It is what allows us to scale virtually infinitely. Eventual consistency is completely fine for lots of usecases: Facebook News Feed (who cares if those status updates show up a few moments earlier or later?), or even static data (a shop which changes its product assortment only once a week during a maintenance timeframe).
Of course there are times where consistent data is crucial: everything involving real money flowing, mission-critical data used for real time status monitoring, etc. This is why Datastore has "Transactions". Every database action executed within a transaction is consistent. However, if consistency can't be assured because someone else is changing that data at the same time transactions fail and you have to retry them for example.
For a much more detailed explanation check out this article: Balancing Strong and Eventual Consistency with Google Cloud Datastore