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Glossary
This page attempts to define some of the terms used in this specification.
Data grids, or IMDGs (In-memory data grids) are, according to Gartner, defined as:
IMDGs implement the notion of a "distributed, in-memory virtual data store" (typically called the data grid, but at times called the "cache" or "space" for historical reasons) by clustering the central memory (RAM) of multiple computers over a network. This allows applications to deal with very large (up to multiple petabytes in size, in some user experiences) in-memory data stores, and leverage fast and scalable access to data. IMDGs provide the mechanisms and APIs that presents to applications the memory of the clustered computers as a uniform, integrated data store. Applications don't need to know in which computer's RAM a given data object is stored to retrieve it. The IMDG runtime retrieves the required object across the data grid in a location-transparent way, while managing such issues as security, data integrity, availability and recovery, in case of system crashes.
The IMDG concept has been explored in academia for almost three decades as an example in the context of the research about the "tuple/space" computing model carried out in the 1980s at Yale University (David Gelernter's Project Linda). IMDG products have been in the market since the early 2000s, and thus have reached a notable degree of technical maturity and adoption rate.