差异:

YAML, depending on how you use it, can be more readable than JSON JSON is often faster and is probably still interoperable with more systems It's possible to write a "good enough" JSON parser very quickly Duplicate keys, which are potentially valid JSON, are definitely invalid YAML. YAML has a ton of features, including comments and relational anchors. YAML syntax is accordingly quite complex, and can be hard to understand. It is possible to write recursive structures in yaml: {a: &b [*b]}, which will loop infinitely in some converters. Even with circular detection, a "yaml bomb" is still possible (see xml bomb). Because there are no references, it is impossible to serialize complex structures with object references in JSON. YAML serialization can therefore be more efficient. In some coding environments, the use of YAML can allow an attacker to execute arbitrary code.

观察:

Python programmers are generally big fans of YAML, because of the use of indentation, rather than bracketed syntax, to indicate levels. Many programmers consider the attachment of "meaning" to indentation a poor choice. If the data format will be leaving an application's environment, parsed within a UI, or sent in a messaging layer, JSON might be a better choice. YAML can be used, directly, for complex tasks like grammar definitions, and is often a better choice than inventing a new language.

差异:

YAML, depending on how you use it, can be more readable than JSON JSON is often faster and is probably still interoperable with more systems It's possible to write a "good enough" JSON parser very quickly Duplicate keys, which are potentially valid JSON, are definitely invalid YAML. YAML has a ton of features, including comments and relational anchors. YAML syntax is accordingly quite complex, and can be hard to understand. It is possible to write recursive structures in yaml: {a: &b [*b]}, which will loop infinitely in some converters. Even with circular detection, a "yaml bomb" is still possible (see xml bomb). Because there are no references, it is impossible to serialize complex structures with object references in JSON. YAML serialization can therefore be more efficient. In some coding environments, the use of YAML can allow an attacker to execute arbitrary code.

观察:

Python programmers are generally big fans of YAML, because of the use of indentation, rather than bracketed syntax, to indicate levels. Many programmers consider the attachment of "meaning" to indentation a poor choice. If the data format will be leaving an application's environment, parsed within a UI, or sent in a messaging layer, JSON might be a better choice. YAML can be used, directly, for complex tasks like grammar definitions, and is often a better choice than inventing a new language.

如果你不需要YAML有而JSON没有的任何特性，我更喜欢JSON，因为它非常简单，并且得到广泛支持(有很多语言的库)。YAML更复杂，支持更少。我不认为解析速度或内存使用会有太大的不同，而且可能不是程序性能的主要部分。

由于这个问题现在在搜索YAML和JSON时非常突出，值得注意的是两者之间一个很少被引用的区别:许可证。JSON声称拥有一个JSON用户必须遵守的许可(包括法律上模棱两可的“应使用代表善，而不是恶”)。YAML没有这样的许可声明，这可能是一个重要的区别(对您的律师来说，如果不是对您来说)。

如果您关心更好的解析速度，那么可以选择将数据存储在JSON中。我必须从其他用户修改文件的位置解析数据，因此我使用YAML，因为与JSON相比，它提供了更好的可读性。 你还可以在YAML文件中添加注释，这在JSON文件中是做不到的。

从技术上讲，YAML是JSON的超集。这意味着，至少在理论上，YAML解析器可以理解JSON，但不一定反过来。

在“YAML:与JSON的关系”一节中可以看到官方规范。

总的来说，我喜欢YAML的某些东西是JSON中没有的。

正如@jdupont指出的，YAML在视觉上更容易看。事实上，YAML主页本身就是有效的YAML，但是它很容易被人阅读。 YAML能够使用“锚”引用YAML文件中的其他项。因此，它可以像在MySQL数据库中一样处理关系信息。 YAML在YAML文件中嵌入其他序列化格式(如JSON或XML)方面更加健壮。

在实践中，最后两点可能对您或我所做的事情都不重要，但从长远来看，我认为YAML将是一种更健壮、更可行的数据序列化格式。

现在，AJAX和其他web技术倾向于使用JSON。YAML目前更多地用于脱机数据处理。例如，它默认包含在基于c语言的OpenCV计算机视觉包中，而JSON则没有。

您将发现JSON和YAML的C库。YAML的库往往更新，但我过去使用它们没有遇到过麻烦。参见Yaml-cpp的例子。