BigMemory differs from traditional caching solutions in its memory storage strategy.
BigMemory在内存存储策略上有别于传统的缓存解决方案。
Developers tune current commercial Web caching solutions for specific types of situations and data.
开发人员为特定类型的情况和数据调整当前的商业Web高速缓存解决方案。
Traditionally, caching solutions have sought to avoid these issues by distributing the data over a cluster of caching nodes.
传统的缓存解决方案为了规避这些问题，都将数据分布在缓存节点组成的集群上。
While Memcached stoked interest and demand for caching solutions, faster, standards compliant implementations will likely have a place at the table as well.
虽然Memcached激发了大家对缓存解决方案的兴趣和需求，但更快、符合标准的实现也会有一席之地。
In-memory caching solutions such as IBM solidDB move the database off of relatively slow hard drives into relatively fast ram, dramatically improving response time.
诸如ibmsoliddb之类的内存中缓存解决方案将数据库从相对较慢的硬盘驱动器转移到相对较快的RAM，大大提升响应速度。
An in-memory database caching capability ACTS as a front end to a back-end database in these tiered solutions.
在这些分层解决方案中，有一个内存中的数据库缓存功能，作为后端数据库的前端。
Then developers, endowed with an appreciation for caching, start adding caching to new projects and solutions at the start instead of waiting for performance issues.
然后，认为缓存很不错的开发人员在新项目和解决方案一开始就会引入缓存，而不是等到出现性能问题的时候才加以引入。
Caching, widely used to improve performance, has been used successfully in many solutions to address the performance issue.
缓存广泛用于提高性能，已成功地应用于很多解决方案中来解决性能问题。
If the workload is a read mostly workload, then solutions like caching with optimistic locking work well.
如果工作负荷主要是读取，那么诸如使用最优锁定进行缓存的解决方案可以很有效。
In the short term, you will see many web caching experts redesign their tools and solutions to become more web service savvy.
从短期来看，您将看到许多Web高速缓存专家都重新设计他们的工具和解决方案以变得更加通晓Web服务。
Now that you have explored cache systems and created a generic cache object, you can learn how to integrate caching in other web service solutions.
既然您已经探索了高速缓存系统并且创建了一个通用的高速缓存对象，您可以学习如何在其他的Web服务解决方案中集成高速缓存了。
With caching, the performance difference between using static stubs and adapter-based solutions is fairly minor.
通过应用缓存，使用静态存根与基于适配器的解决方案之间的差异相对较小。
These solutions include inspecting of network connecting, client data caching, data synchronizing, and handling data concurrency.
这些解决方案包括网络连接状态的监测、客户端数据的缓存、数据的同步和数据并发处理。
Blue Coat offers caching and compression solutions.
蓝色大衣提供缓存和压缩解决方案。
After analyzing characteristics of data caching, several solutions to problem of cache coherence are offered and a new directory lists method is designed for the cache system.
并在此基础上，通过分析数据缓存系统的特点，提出针对缓存一致性问题的解决方法，其中重点阐述为本文所提缓存系统模型而设计的一种改进方法，即目录表法。
After analyzing characteristics of data caching, several solutions to problem of cache coherence are offered and a new directory lists method is designed for the cache system.
并在此基础上，通过分析数据缓存系统的特点，提出针对缓存一致性问题的解决方法，其中重点阐述为本文所提缓存系统模型而设计的一种改进方法，即目录表法。
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