问题描述
Cassandra不像RDBMS那样遵守ACID，而是CAP。所以Cassandra从AP中挑出AP并留给用户以调整一致性。我绝对不能将Cassandra用于核心银行业务交易，因为C *有点不一致。
但Cassandra写的速度非常快，这对于OLTP来说非常有用。
我可以将C *用于OLAP，因为读取速度非常快，这对报告也很有用。
所以我明白，只有当你的应用程序不需要你的数据在一段时间内保持一致时，C *才是好的，但读写应该很快？
如果我的理解是正确的，请列举一些应用程序？
ACID是关系数据库的属性，其中BASE是大多数nosql数据库和Cassandra都是其中之一。 CAP理论只是解释了分布式系统中一致性，可用性和分区容错的问题。 Cassandra的好处在于它具有可调整的一致性，因此您可以非常一致（以分区容差为代价），因此OLTP是可行的。正如Phact所说，甚至有一些银行在Cassandra之上建立了他们的交易软件。由于分区行存储限制了其功能，所以OLAP也是可行的，但Cassandra并非如此。你需要像Spark那样能够完成所需的复杂查询。
Cassandra does not comply with ACID like RDBMS but CAP. So Cassandra picks AP out of CAP and leaves it to the user for tuning consistency.I definitely cannot use Cassandra for core banking transaction because C* is slightly inconsistent.But Cassandra writes are extremely fast which is good for OLTP.I can use C* for OLAP because reads are extremely fast which is good for reporting too.So i understood that C* is good only when your application do not need your data to be consistent for some amount of time but reads and writes should be quick?If my understanding is right kindly list some applications?
ACID are properties of relational databases where BASE are properties of most nosql databases and Cassandra is one of the. CAP theorem just explains the problem of consistency, availability and partition tolerance in distributed systems. Good thing about Cassandra is that it has tunable consistency so you can be pretty much consistent (at the price of partition tolerance) so OLTP is doable. As phact said there are even some banks that built their transaction software on top of Cassandra. OLAP is also doable but not with just Cassandra since its partitioned row storage limits its capabilities. You need to have something like Spark to be able to do complex queries required.
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