However, SAP HANA and the like use in-memory computing techniques to accelerate the performance of specific vendor-oriented applications.

In-memory computing involves storing data in the main random access memory (ram) of specialised servers instead of in complex relational databases running on relatively slow disk drives.

As the demand for real-time access to big data accelerates and expectations for optimal performance increase, sophisticated data persistence becomes invaluable.

Your organization has a typical x86 server which has somewhere between 32GB to 256GB of RAM. While this is a decent amount of memory for a single computer, that's not enough to store many of today ...

In-memory computing can deliver a 1000X increase in speed in addition to the ability to scale out to handle petabytes of in-memory data for new and existing applications.

In-Memory Computing can accelerate traditional applications by using a memory first design. Applicable to a wide range of domains, In-Memory Computing and In-Memory Data Grids take advantage of the ...

In-memory computing: Where fast data meets big data The evolution of memory technology means we may be about to witness the next wave in computing and storage paradigms.

Snabe predicted that in-memory computing will be the dominant computer architecture in future, taking over from the separate hard drive and memory architecture that computers have today.

A new white paper from GridGain explores why demand is growing for IMC platforms and what's next for the world of in-memory computing.

As noted at the beginning of this article series last week, an initial dive into in-memory computing meant questioning whether this was just another of those buzz words or whether there was some meat ...

As we continue through 2021 and in-memory computing platforms mature, we will see the number of industries and companies adopting these solutions con­tinue to grow. This trend will last far beyond the ...