The pricing is a bit hard to compare. Stax is still in beta and it hasn't announced prices. Aptana has just four settings that tie everything together. The amount of disk space you get is tied to the amount of memory you allocate. One hour of CPU time can vary between $0.027 and $0.359. You pay this whether your machine is doing something or not.
Google, on the other hand, breaks up the bill and charges for bandwidth, stored data, e-mail, and CPU time. The price of $0.10 for the CPU seems more expensive because the cost is computed per thread. I was easily able to handle four or five requests at the same time with the cheapest setting on Aptana Cloud. But this doesn't mean that Aptana's cloud is wildly cheaper, because Google's cloud doesn't bill you if there are no requests coming in. It's very difficult to compare these offerings, and I'm sure that different applications will run up very different bills on each service.
These vendors' approaches are bound to evolve in the future as the companies try to figure out the right price and the real cost of offering these services. It may turn out, for instance, that the clouds need so many extra servers at the peak times that they need to charge enough to cover their costs during the down time. Or maybe there will be enough users at different times to spread out the demand. While I think Aptana's prices are pretty much similar to the standard prices for VPS on shared servers, Google's choices are less solid because they depend upon predictions of what people will do.
No one is certain how this model will evolve, but the future of cloud systems like these depends heavily on the decisions that everyone makes. A company with its own dedicated servers in its own datacenter can be a lone wolf, but anyone who chooses a cloud must adapt to working together. Although all of these systems erect firewalls that separate the applications from one another, there will be secondary effects. If you end up on a cluster with a company that buys a Super Bowl ad, everyone in the neighborhood is affected for a few minutes. If demand for a certain service isn't high enough to pay the rent, the host is going to need to boost rates.
These are just some of the questions that emerge as the words "Java" and "cloud" are brought together. While the new offerings are ostensibly built for Java, they open the door to many other languages because some of the more popular ones today run on top of Java. Some Ruby programmers, for instance, switch over to JRuby when they feel that Java's threading model offers better support. Jython is another favorite way to run Python with all of the robustness that can be borrowed from the JVM.
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