[官方]Cascading不同于PIG和HIVE吗?

Cascading | Cascading
http://www.cascading.org/projects/cascading/

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级联是如何不同于PIG和HIVE吗?
应用程序开发时,Pig和Hive有缺点在处理复杂性和测试,而层叠构建应用的扩展。 猪,简单的问题很容易解决,但是困难的问题变得相当复杂。 蜂巢,语言是不符合ANSI SQL标准,使其适用性和互操作性与现有SQL系统具有挑战性。 此外,它是不确定的,这使得它的行为很难预测相比,层叠的确定的计划。
Pig和Hive通常需要更多代码时集成和整合业务逻辑。 级联分离业务逻辑和集成逻辑,并已经内置的系统集成能力。 与Pig和Hive,难以构建复杂工作流的数据,和同样很难排除您的数据的应用程序。 级联允许开发人员执行单元测试和测试驱动的大规模部署最佳实践。

When it comes to application development, both Pig and Hive have shortcomings when dealing with complexity and testing, while Cascading applications are built to scale. With Pig, easy problems can be easily solved, but the harder problems become quite complicated. With Hive, the language is not compliant with ANSI SQL standards, which makes its applicability and interoperability with existing SQL systems challenging. Furthermore, it is non-deterministic, which makes its behavior difficult to predict when compared to Cascading’s deterministic planner. Both Pig and Hive will generally require significantly more code when it comes to integration and incorporating business logic. Cascading separates business logic and integration logic and has system integration capabilities already built-in. Also, with Pig and Hive, it is notoriously difficult to build complex data workflows, and equally as hard to troubleshoot your data applications. Cascading allows developers to unit test and execute test-driven deployment best practices at scale.