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.

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.

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 ...

In-memory computing specialist GridGain Systems Inc. said Nov. 3 that its data fabric code has been accepted by the Apache Software Foundation’s incubator program under the name “Apache Ignite.” ...

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 ...