How does an in-memory data grid improve the performance, scalability and reliability of a relational database (RDBMS)?
The fundamental problems with both database replication and database partitioning is the reliance on the performance of the file system/disk and the complexity involved in setting up database clusters. No matter how you turn it around, file systems are fairly ineffective when it comes to concurrency and scaling. This is pure physics: disk storage suffers severe latency because each data access must go through serialization/de-serialization, as well as mapping from binary format to a usable format. This puts hard limits on latency. In addition, latency is often severely affected by lack of scalability. So putting the two together makes file systems — and databases, which heavily rely on them — suffer from limited performance and scalability. These database patterns evolved under the assumption that memory is scarce and expensive, and that network bandwidth is a bottleneck. Today, memory resources are abundant and available at a relatively low cost. So is bandwidth. These two facts all
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