XML与关系服务之间紧密集成。
There is tight integration between both XML and relational services.
可以使用它把XML数据与关系数据结合在一起。
XML数据按照原生的树格式与关系数据分开存储。
XML data is stored in a native tree format, separate from the relational data.
与关系数据库相比，面向对象模型支持更丰富的关系
Richer relationships allowed by object orientation that aren't supported by relational databases
mongodb索引与关系数据库中的索引十分相似。
MongoDB indexes are quite similar to relational databases indexes.
此外，您也许还有与关系本身相关的需要建模的其它信息。
Additionally, you may have other information associated with the relationship itself that you need to model.
正如其名字代表的一样，该库提供与关系数据库交互的标记。
As its name suggests, this library provides tags for interacting with relational databases.
XML数据可以按照原有的层次化格式与关系数据一起存储。
Instead, XML data can be stored intact in its native hierarchical format alongside relational data.
使用与关系数据库一起提供的块载入工具来初始化数据库表。
Use the bulk load tools that are provided with relational databases to initialize database tables.
它提供了连接XML数据与关系型数据的最简便途径。
It provides the easiest means to join XML data and relational data.
使用两种框架的目的都是为了减少与关系数据库有关的开发时间。
Both frameworks aim to reduce the development time associated with working with relational databases.
您可以通过组合方式查询XML数据与关系型数据。
You can query XML data and relational data in a combined manner.
快乐，幸福和成就感是生命中看不到的东西。爱，希望，和平与关系。
Joy, happiness, and fulfillment are found in the invisible things of life: love, hope, peace, and relationships.
在此情况下，其中包含的条目数目与关系的目标端的实例的数目一样多。
In that case, there will be as many entries as there are instances at the target end of the relationship.
更大的XML文档存储在与关系数据分离的数据区域中，它们也可以压缩。
Larger XML documents that reside in a data area separate from relational data can also be compressed.
XML中次序的重要性与关系数据模型中缺少固有次序形成了鲜明对比。
The importance of order in XML contrasts sharply with the absence of intrinsic order in the relational data model.
这是一个面向对象的软件项目，使用UML来描述系统中的各种概念与关系。
This will be an object-oriented project using the Unified Modeling Language (UML) to represent concepts and relationships.
您可以选择将说明与关系图的某个部分联系起来，如图1 所示。
Optionally, you can connect a note to a part of the diagram, as shown in Figure 1.
cid属性的值被传递给sqlquery函数，以将其与关系cid值进行比较。
The value of the cid attribute is passed to the sqlquery function to compare it to the relational cid value.
当您编写与关系数据库（例如DB2）交互的计算机代码时，必须考虑两个关键要素。
When you write computer code that interacts with relational databases such as DB2, you have to consider two key items.
与关系数据库的SQL非常相似，Xpath支持导航到一个XML文档中的各个地方。
Much like SQL for relational databases, Xpath enables you to navigate to various places in an XML document.
这些应用会经常与关系数据库或者其他信息系统——比如面向消息的中间件——进行交互。
These applications frequently interact with relational databases and other information systems such as message-oriented middleware.
这可能是使用OODBMS最棘手的部分，因为对象数据库使用与关系数据库不同的一致性概念。
This is probably the trickiest part of working with an OODBMS because an object database USES a different notion of identity from a relational database.
XML索引存储在与关系索引相同的索引页面中，因此提供与关系索引相似的访问时间。
XML indexes are stored in the same index pages as relational indexes, thus providing similar access times when compared with relational indexes.
ManagerBean向导会显示出一个数据库中包含的关键字与关系，并允许您去定义它们。
The Manager Bean wizard displays, and allows you to define keys and relationships contained in a database.
和在普通HTML页面上一样，输入表单字段的名称必须与关系型更新数据源中使用的参数名称匹配。
Just as on a normal HTML page, the input form fields must have names that match the name of the parameters used in the relational update feed.
设计时的映射结果通常为联合视图，与关系数据库视图类似，可以随后在联合服务器上进行部署或创建。
The result of mapping in design time are typically federated views, similar to relational database views, which then can be deployed or created on the federation server.
使用Viper 的混合模型，我们看到的是一个转折点与关系型数据库出现时的意义一样重大。
With Viper’s hybrid model, what we’re seeing is an inflection point every bit as significant as when relational databases appeared.
占用的存储空间少于32kb的小型XML文档可以与关系数据一起内联存储在同一行中，可以对整行进行压缩。
Small XML documents that occupy less than 32kb of storage space can be inlined with any relational data present in the same row, and the entire row can be compressed.
我们可以创建两个数据集，以直接得到工作性的信息与关系，然后合并两个数据集以找到所有工作项目之间的关系。
We can create two data sets to get the work item's information and the relationship information directly, and then join the two data sets to find the relationships between of all work items.
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