But this approach is slow and expensive, and sometimes not even feasible, because some data sources are too big to be replicated ... pushing down as much processing as possible to the data sources. 2.

In the ever-expanding realm of data processing and analytics, two heavyweight contenders − massively parallel processing (MPP) and big data − have been vying for dominance. Each brings its own ...

But Big Data's not all about MapReduce. There’s another computational approach to distributed query processing, called Massively Parallel Processing, or MPP. MPP has a lot in common with MapReduce.

Fujitsu Laboratories today announced that it has developed new parallel distributed data processing technology that enables pools of big data as well as continuous inflows of new data to be ...

and data processing units (DPUs). However, what almost all modern software has in common is that it can run in parallel, meaning that it can be broken down and have different tasks run multiple ...

In-memory data grid (IMDG) specialist Hazelcast Inc. yesterday launched a new distributed processing engine for Big Data streams. The open-source, Apache 2-licenced Hazelcast Jet is designed to ...