Forrest 2015年第三季度内存网格分析报告
Forrester于2015年Q3发布了最新的内存数据网格分析报告，PDF版本可以下载。 关于内存数据库(IMDB)的评测可参见 Forrest 2015年第三季度内存数据库分析报告 现代化应用的需求陷入了两难选择，一方面需要更多更炫的功能，更多更快的数据访问，一方面又架构可灵
Forrester于2015年Q3发布了最新的内存数据网格分析报告，PDF版本可以下载。
关于内存数据库(IMDB)的评测可参见 Forrest 2015年第三季度内存数据库分析报告
现代化应用的需求陷入了两难选择，一方面需要更多更炫的功能，更多更快的数据访问，一方面又架构可灵活横向扩展以满足性能和大规模并行访问的需求。
Forrester 对于内存数据网格(IMDG)的定义为：
Software tools and technologies that are architected to use chip-based random access memory (RAM) distributed across multiple nodes to accelerate performance and achieve scalability of data access and compute.
这里的关键是分布式，可扩展，相对于IMDB的集中式。虽然IMDB也可以做sharding，但这是外部的分布，不是IMDG为内部自动分布。
其实有些IMDB的产品也具有IMDG的特性，例如TimesTen的cache grid，但本质上TimesTen还是IMDB。
IMDG提供可扩展的性能依赖于：
1. 使用内存减少数据访问的延迟
内存速度：RAM is 58,000 times faster than disk and 2,000 times faster than solid-state drives (SSD)
内存价格的下降
2. 在节点间分布数据实现线性扩展
3. 在节点间复制数据实现高可用
4. 在数据中心间同步数据实现灾备
原文中的几张概念图还不错，可以参考。
IMDG的典型使用场景为：
1. 缓存以消除传统数据库系统的数据瓶颈
数据库系统的横向扩展性较差，通过IMDG可以消除瓶颈，应对更复杂，更高并行度的访问。IMDG不仅可缓存数据库，对于大机，文件系统等都可以缓存。在这种多数据源的场景，性能问题会更加明显
2. 缓存零食临时数据
临时的会话数据和共享数据，如在线游戏
3. 现代化应用的主存储
作为主存而非缓存，也就是System Of Record而非System Of Reference。例如Savvy
4. 内存NoSQL数据库
IMDG也是Key-Value数据库，只不过运行在内存中，可以支持ACID。（ACID这个我不确定）
5. 用于实时数据集成的数据服务Fabric
将多个数据源的数据汇集到IMDG中
6. 具有内存速度的Comptute Grid
例如执行MapReduce操作，并行计算等。可以替代Hadoop+Spark的批处理架构
评测结果如下图，可以看到Oracle Coherence位居第一。而在之前的IMDG评测中, Oracle凭借TimesTen和12c DBIM位居第二，可见在内存计算领域，Oracle比较强大。
Oracle的Coherence是2007年从Tangosol收购的，同样TimesTen也是2005年收购的，只有12c DBIM是源于自己开发。
扩展阅读：
The Forrester Wave?: NoSQL Document Databases, Q3 2014
The Forrester Wave?: NoSQL Key-Value Databases, Q3 2014
Apache Spark Is Powerful And Promising
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