The problems you are finding are why RDBMS specialists view some of the alternative systems with a jaundiced eye. Yes, the alternative systems handle certain specific requirements extremely fast, but as soon as you want to do something else with the same data, the fleetest suddenly becomes the laggard. By contrast, an RDBMS typically manages the variations with greater aplomb; it may not be quite as fast as the fleetest for the specialized workload which the fleetest is micro-optimized to handle, but it seldom deteriorates as fast when called upon to deal with other queries.
Compared to traditional RDBMS, these systems make improvements in some aspect (scalability, availability or simplicity) by trading-off other aspects (reduced query capability, eventual consistency, horrible performance for certain operations).
Think of these not as replacements of the traditional database, but they are specialized tools for a known, specific need.
Take Amazon Simple DB for example, SDB is basically a huge spreadsheet, if that is what your data looks like, then it probably works well and the superb scalability and simplicity will save you a lot of time and money.
If your system requires very structured and complex queries but you insist with one of these cool new solution, you will soon find yourself in the middle of re-implementing a amateurish, ill-designed RDBMS, with all of its inherent problems.
In this respect, if you do not know whether these will suit your need, I think it is actually better to do your first few iterations in a traditional RDBMS because they give you the best flexibility and capability especially in a single server deployment and under modest load. (see CAP Theorem).
Once you have a better idea about what your data will look like and how will they be used, then you can match your need with an alternative solution.
If you want the simplicity of a cloud hosted solution, but needs a relational database, you can check out: Amazon Relational Database Service
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您所发现的问题就是为什么 RDBMS 专家对某些替代系统抱有偏见的看法。 是的，替代系统可以非常快地处理某些特定要求，但是一旦您想使用相同的数据做其他事情，最快的系统就会突然变得落后。 相比之下，RDBMS 通常可以更加沉着地管理变化。 对于专门的工作负载来说，它可能不如fleetest那么快，而fleetest经过微优化来处理，但是当被要求处理其他查询时，它很少会像fleetest一样快地恶化。
The problems you are finding are why RDBMS specialists view some of the alternative systems with a jaundiced eye. Yes, the alternative systems handle certain specific requirements extremely fast, but as soon as you want to do something else with the same data, the fleetest suddenly becomes the laggard. By contrast, an RDBMS typically manages the variations with greater aplomb; it may not be quite as fast as the fleetest for the specialized workload which the fleetest is micro-optimized to handle, but it seldom deteriorates as fast when called upon to deal with other queries.
新的解决方案并不是灵丹妙药。
与传统的 RDBMS 相比，这些系统在某些方面（可扩展性、可用性或简单性）进行了改进，但在其他方面（查询能力降低、最终一致性、某些操作的糟糕性能）进行了权衡。
不要将它们视为传统数据库的替代品，但它们是满足已知特定需求的专用工具。
以Amazon Simple DB为例，SDB基本上是一个巨大的电子表格，如果这就是您的数据的样子，那么它可能运行良好，并且卓越的可扩展性和简单性将为您节省大量时间和金钱。
如果您的系统需要非常结构化和复杂的查询，但您坚持使用这些很酷的新解决方案之一，那么您很快就会发现自己正在重新实现一个业余的、设计不良的 RDBMS，并且存在所有固有的问题。
在这方面，如果您不知道这些是否适合您的需求，我认为在传统 RDBMS 中进行前几次迭代实际上更好，因为它们为您提供了最好的灵活性和功能，尤其是在单个服务器中部署并在适度负载下。 （参见CAP 定理）。
一旦您更好地了解您的数据是什么样子以及如何使用它们，您就可以使用替代解决方案来满足您的需求。
如果您想要云托管解决方案的简单性，但需要关系数据库，您可以查看：Amazon Relational Database Service
The new solutions are not silver bullets.
Compared to traditional RDBMS, these systems make improvements in some aspect (scalability, availability or simplicity) by trading-off other aspects (reduced query capability, eventual consistency, horrible performance for certain operations).
Think of these not as replacements of the traditional database, but they are specialized tools for a known, specific need.
Take Amazon Simple DB for example, SDB is basically a huge spreadsheet, if that is what your data looks like, then it probably works well and the superb scalability and simplicity will save you a lot of time and money.
If your system requires very structured and complex queries but you insist with one of these cool new solution, you will soon find yourself in the middle of re-implementing a amateurish, ill-designed RDBMS, with all of its inherent problems.
In this respect, if you do not know whether these will suit your need, I think it is actually better to do your first few iterations in a traditional RDBMS because they give you the best flexibility and capability especially in a single server deployment and under modest load. (see CAP Theorem).
Once you have a better idea about what your data will look like and how will they be used, then you can match your need with an alternative solution.
If you want the simplicity of a cloud hosted solution, but needs a relational database, you can check out: Amazon Relational Database Service