最近有很多关于卡桑德拉的话题。

Twitter, Digg, Facebook等都在使用它。

什么时候有意义:

使用卡桑德拉, 不用卡桑德拉,还有 使用RDMS而不是Cassandra。


当前回答

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.

其他回答

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。

在部署Cassandra的过程中与某人交谈,它不能很好地处理多对多。他们正在做初步测试。我和Cassandra的顾问谈过这个问题,他说如果你有这样的习题集,他就不建议你这么做。

Apache cassandra是一个分布式数据库,用于跨许多商用服务器管理大量结构化数据,同时提供高可用性服务,没有单点故障。

该架构完全基于上限定理,即可用性和分区容忍,有趣的是最终一致。

不要使用它,如果你不存储数据卷的机架集群, 如果您不存储时间序列数据,请不要使用, 不要使用如果你不分区你的服务器, 如果你要求强烈的一致性,请不要使用。

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)

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。