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

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 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.

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 has come a long way over the last few years. Today’s mature, cost-effective solutions deliver the massive application speed and scalability organizations need to power ...

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 ...

In-memory databases have been in existence since the late 70s, but only now do we have the platforms needed and the high-speed processors to make in-memory computing economic and useful.

The evolution of memory technology means we may be about to witness the next wave in computing and storage paradigms. If Hadoop disrupted by making it easy to utilize pooled commodity hardware ...

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.” ...

In-Memory Computing Challenges Come Into Focus Researchers digging into ways around the von Neumann bottleneck.