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An in-memory data grid builds versatility into systems and also allows for different kinds of data processes. Part of the strategy of an in-memory data grid is to avoid the traditional input/output bottlenecks encountered with relational databases. It does this by using an object-oriented design rather than a relational database structure. For example, some types of in-memory data grid are implemented as Java object grids.
The use of in-memory data grids is also associated with the use of certain open-source programs like Apache Hadoop for analytics. Solutions are combining in-memory data grids with these analytics platforms, and the Hadoop distributed file system uses a similar object-oriented approach. The in-memory data grid is becoming an alternative to traditional relational databases for scalability.