another situation that makes the choice easier is when you want to use aggregate function like sum, min, max, etcetera and complex queries (like in the financial system mentioned above) then a relational database is probably more convenient then a nosql database since both are not possible on a nosql databse unless you use really a lot of Inverted indexes. When you do use nosql you would have to do the aggregate functions in code or store them seperatly in its own columnfamily but this makes it all quite complex and reduces the performance that you gained by using nosql.

让我们来读一些真实的案例:

http://planetcassandra.org/apache-cassandra-use-cases/

本文地址:http://planetcassandra.org/blog/post/agentis-energy-stores-over-15-billion-records-of-time-series-usage-data-in-apache-cassandra

他们详细阐述了不选择MySql的原因，因为数据库同步太慢。

(也是由于2- phase commit, FK, PK)

Cassandra基于Amazon Dynamo纸

特点:

稳定

高可用性

备份性能良好

读写比HBase好，(java中的BigTable克隆)。

wiki http://en.wikipedia.org/wiki/Apache_Cassandra

他们的结论是:

We looked at HBase, Dynamo, Mongo and Cassandra. 

Cassandra was simply the best storage solution for the majority of our data.

截至2018年，

如果你需要支援，我建议你用ScyllaDB代替经典的cassandra。

Postgres kv插件也比cassandra快。无论如何不会有多实例可伸缩性。

你应该问自己以下问题:

(Volume, Velocity) Will you be writing and reading TONS of information , so much information that no one computer could handle the writes. (Global) Will you need this writing and reading capability around the world so that the writes in one part of the world are accessible in another part of the world? (Reliability) Do you need this database to be up and running all the time and never go down regardless of which Cloud, which country, whether it's VM , Container, or Bare metal? (Scale-ability) Do you need this database to be able to continue to grow easily and scale linearly (Consistency) Do you need TUNABLE consistency where some writes can happen asynchronously where as others need to be certified? (Skill) Are you willing to do what it takes to learn this technology and the data modeling that goes with creating a globally distributed database that can be fast for everyone, everywhere?

如果在这些问题中，你认为“可能”或“不”，你应该用别的词。如果你对所有问题的答案都是“当然”，那么你应该用卡桑德拉。

当你可以在一个盒子上做所有事情时，使用RDBMS。它可能比大多数方法都简单，任何人都可以使用它。

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.

它不支持跨 表。 不支持二级索引。 二级索引必须依赖Elastic search /Solr，并且必须编写自定义同步组件。 非ACID兼容系统。 查询支持有限。

Cassandra是个不错的选择，如果:

您不需要DB中的ACID属性。 DB上会有大量的写操作。 需要与大数据、Hadoop、Hive和Spark集成。 需要实时数据分析和生成报告。 有一个强大的容错机制的要求。 有一个齐次系统的要求。 调优需要大量的自定义。