Mongodb有非常强大的聚合函数和一个富有表现力的聚合框架。它具有许多开发人员习惯于从关系数据库世界中使用的特性。例如，它的文档数据/存储结构允许比Cassandra更复杂的数据模型。

当然，所有这些都是有代价的。因此，当您选择数据库(NoSQL、NewSQL或RDBMS)时，请考虑您要解决的问题和可伸缩性需求。没有一个数据库可以完成所有的工作。

在这里，我将重点介绍一些重要的方面，这些方面可以帮助你决定是否真的需要卡桑德拉。这个清单并不详尽，只是我脑海中最重要的一些观点

Don't consider Cassandra as the first choice when you have a strict requirement on the relationship (across your dataset). Cassandra by default is AP system (of CAP). But, it supports tunable consistency which means it can be configured to support as CP as well. So don't ignore it just because you read somewhere that it's AP and you are looking for CP systems. Cassandra is more accurately termed “tuneably consistent,” which means it allows you to easily decide the level of consistency you require, in balance with the level of availability. Don't use Cassandra if your scale is not much or if you can deal with a non-distributed DB. Think harder if your team thinks that all your problems will be solved if you use distributed DBs like Cassandra. To start with these DBs is very simple as it comes with many defaults but optimizing and mastering it for solving a specific problem would require a good (if not a lot) amount of engineering effort. Cassandra is column-oriented but at the same time each row also has a unique key. So, it might be helpful to think of it as an indexed, row-oriented store. You can even use it as a document store. Cassandra doesn't force you to define the fields beforehand. So, if you are in a startup mode or your features are evolving (as in agile) - Cassandra embraces it. So better, first think about queries and then think about data to answer them. Cassandra is optimized for really high throughput on writes. If your use case is read-heavy (like cache) then Cassandra might not be an ideal choice.

在评估分布式数据系统时，您必须考虑CAP定理——您可以选择以下两个:一致性、可用性和分区容差。

Cassandra是一个可用的、支持最终一致性的分区容忍系统。要了解更多信息，请参阅我写的这篇博客文章:NoSQL系统的可视化指南。

除了上面给出的关于何时使用和何时不使用Cassandra的答案外，如果你决定使用Cassandra，你可能会考虑不使用Cassandra本身，而是使用它的众多表亲之一。

上面的一些答案已经指出了各种“NoSQL”系统，它们与Cassandra有许多相同的属性，有一些或大或小的差异，并且可能比Cassandra本身更适合您的特定需求。

Additionally, recently (several years after this question was originally asked), a Cassandra clone called Scylla (see https://en.wikipedia.org/wiki/Scylla_(database)) was released. Scylla is an open-source re-implementation of Cassandra in C++, which claims to have significantly higher throughput and lower latencies than the original Java Cassandra, while being mostly compatible with it (in features, APIs, and file formats). So if you're already considering Cassandra, you may want to consider Scylla as well.

Cassandra是一个特定问题的答案:当您有太多数据，以至于无法在一台服务器上存储时，您该怎么办?如何将所有数据存储在多个服务器上，同时不破坏银行账户，不让开发人员抓狂?Facebook每天都会收到4tb的压缩数据。这个数字很可能在一年内增长两倍以上。

如果您没有这么多数据，或者您有数百万美元来支付企业Oracle/DB2集群安装费用，以及安装和维护它所需的专家，那么您可以使用SQL数据库。

然而，Facebook不再使用cassandra，现在几乎只使用MySQL，在应用程序堆栈中移动分区，以获得更快的性能和更好的控制。

根据DataStax，当需要Cassandra时，它并不是最好的用例

1-高端硬件设备。 2- ACID兼容，无回滚(银行交易)