Multi-tenant data tier design patterns.
多租户数据层设计模式。
In the data tier, it USES SQL and ODBC.
在数据层，它使用SQL和ODBC。
The MySQL database is used in the data tier.
在数据层中使用MySQL数据库。
We recommend that you install the index data service in the data tier.
我们建议您在数据层安装索引数据服务。
Theory of 3-tiered structure and design and realization of data tier.
三层体系结构理论和数据层的设计实现。
As shown in Figure 9, there are three levels of resource sharing in data tier.
如图9所示，在数据层中有三个资源共享级别。
Added to this mix is the open source database success of MySQL in the data tier.
在这个组合之上，还可以用开放源码数据库MySQL建立数据层。
The middle tier typically connects to the data tier by using a data connection.
中间层通常使用数据连接来连接至数据层。
The data tier cannot be accessed directly from the client in the presentation tier.
数据层不能从表示层中的客户端直接访问。
This model is composed of three tiers: data tier, application tier and presentation tier.
模型框架结构分为数据层、应用服务层和视图层。
A three-tier enterprise architecture consists of a client tier, middle tier, and a data tier.
一个三层的企业架构由客户机层、中间层以及数据层组成。
The Domain Model divides into three portions: a presentation tier, an application tier, and a data tier.
领域模型把应用划分成三个部分：表现层，应用层和数据层。
This design pattern introduces an application server in the middle tier which brokers connections between clients and the data tier.
这种设计模式在中间层中引入了一个应用程序服务器，中间层代理客户端和数据层之间的代理。
These business objects form a layer between the presentation layer and the data tier, resulting in a three-tier application architecture.
这些商务物件会在展示层和资料层之间构成一个层级，形成三层式应用程序架构。
Although you can back up an application tier more easily than a data tier, you must perform many steps when you restore an application tier.
尽管备份应用层比备份数据层更加容易，但在还原应用层时必须执行许多步骤。
The persistent backing of Mongo's cache assures that on a system restart the downstream data tier is not overwhelmed with cache population activity.
MongoDB缓存可以持续支持的能力保证系统重启下游数据层而不干扰缓存的频繁活动。
If you see that the middle tier is becoming the bottleneck, you may have to add more no. of application servers and same is the case with the data tier.
如果你发现中间层正在变成瓶颈，你就必须增加应用服务器的数量，数据层也是同样的状况。
However, the cost of process hopping to the database is still high, thus performance on the data tier is the first place to look when optimizing your code.
然而进程跳跃到数据库的成本依然很高，因此数据层的性能是您在优化代码时首先要考虑的问题。
For example, the data tier and the application tier might be located on the same machine in one topology, whereas the two tiers are located on separate machines in the other topology.
例如，在一个拓扑中数据层和应用层可能位于同一计算机上，而这两层在另一个拓扑中位于不同的计算机上。
For example, in the data repository tier, staging and repository databases can be on different servers, on the same server, or even in the same database under different schemas.
例如，在数据存储库层，登台数据库和存储库数据库可以在不同的服务器上、在同一服务器上或者甚至在不同模式下的同一数据库中。
These so-called "Tier-1" centers make the data available to over 120 "Tier-2" centers for specific analysis tasks.
这些所谓的“一级”中心将为超过120个的“二级”中心提供数据以用于专门的分析任务。
Can we move common data to a separate cache or tier?
我们是否可以将公共数据移动到单独的缓存或层？
The data mart tier contains all the data marts, which are subsets of the data repository module, made simple enough for specific groups of end users to use in their data analysis activities.
数据集市层包含所有的数据集市，这些数据集市是数据存储库模块的子集，以便特定的终端用户组在其数据分析活动中使用起来足够简单。
In this model, the business data warehouse is the collection of data repository databases (module), and the data marts are the databases from the data mart tier.
在该模型中，业务数据仓库是数据存储库数据库(模块)的集合，而数据集市则是数据集市层中的数据库。
The purpose of the data caching tier is to provide scalable, fault tolerant, coherent data grids for your application server tier.
数据缓存层的目的是为您的应用程序服务器层提供一个可伸缩、容错和一致的数据网格。
Let's briefly discuss each tier, starting with the data integration tier.
让我们简要讨论一下每个层，首先从数据集成层开始。
So, conceptually, a DSL solution includes two logical tiers: a data services orchestration tier that supports the referred to system process and a data integration tier.
因此，从概念上讲，DSL解决方案包括两个逻辑层：数据服务编排层(此层支持所引用的系统进程)和数据集成层。
The methods in Listing 4 form the core of the data access tier.
清单4中的方法构成了数据访问层的核心。
At the data services orchestration tier, caching is supported by a specialized data caching service.
在数据服务编排层，缓存由专门的数据缓存服务提供支持。
When a domain object leaves the data access tier, it gets detached from the entity manager.
当域对象离开数据访问层时，它与实体管理器脱离。
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