Your organization has a typical x86 server which has somewhere between 32GB to 256GB of RAM (News - Alert). While this is a decent amount of memory for a single computer, that’s not enough to store many of today’s operational datasets that easily measure in terabytes. This is why there is in-memory computing. But what is it?
In-memory computing means using a type of middleware software that allows one to store data in RAM, across a cluster of computers, and process it in parallel.
Companies like ScaleMP offer virtualization for in-memory high-end computing, which is good for data center consolidation, and significantly reducing capital costs, as well as operational and infrastructure overhead. What’s more, organizations can significantly extend the lifetime of their existing hardware and software by using existing equipment and making it go faster.
Organizations are upgrading IT architectures to take advantage of the low latency processing that in-memory computing offers. Regardless of company size, in-memory is the best way to deliver on high performance requirements.
What could your company do with a faster data processing engine? In-memory platforms can handle large volumes of data from structured, semi-structured, and unstructured data—such as from email, social media, and machine or computer logs.
The possibilities span from boosting operational systems such as predictive workforce analytics and sales forecasting, to customer-facing applications such as intelligent point-of-sale systems.
Hear what ScaleMP had to say about in-memory computing and its solutions straight from this year’s Cloud Expo showroom floor: