Key technologies of spatial data enginer based on multi - data source 多数据源空间数据引擎关键技术问题研究
The function and systematic structural design of spatial database engine for rdbms 的空间数据引擎体系结构框架设计
The desktop data engine 桌面数据引擎。
Applications are freed from hard - coded dependencies on a particular data engine or storage schema 应用程序在编码上不依赖于特定的数据引擎或存储架构。
Sql server mobile represents the best local data engine for devices that are only occasionally connected Sql server mobile只对偶尔连接的设备而言,是最佳的本地数据引擎。
This frees applications from hard - coded dependencies on a particular data engine or even a particular logical model 这样就可以将应用程序从一个靠硬编码关联的特定数据引擎甚至特定的逻辑模型中解放出来。
An additional benefit is that developers can work with a consistent conceptual model across multiple storage engines 一个附带的好处是,开发人员可以在一个稳定的概念模型上进行工作,即使跨越多个数据引擎。
The physical model addresses the capabilities of a particular data engine by specifying storage details such as partitioning and indexing 物理模型则根据特定的数据引擎的情况规定特殊的存储细节,例如索引和表分割。
This paper introduces the concepts and theory of sde ( spatial data engineer ) , and presents some key technologies , such as the model of sde , the efficiency of sde , data consist of multi - user edit , etc 摘要介绍了空间数据引擎的概念和原理,剖析了空间数据模型、引擎效率、多用户编辑的数据一致性、多数据源支持等空间数据引擎的关键技术。
Bde and ado are used to connect different server . sql statements are generated dynamically to provide user with more flexible and effective combined query and indefinite query . some ways to improve maintainability and flexibility of the system are also discussed 论文也探讨了bde和ado两种数据引擎的使用,通过动态生成sql语句进行组合查询和模糊查询,提高查询的效率和灵活性,以及提高系统的适应性和可维护性的一些途径。