ScaleOut Software has integrated Microsoft's powerful LINQ-based query capability into its in-memory data grid, allowing applications to perform fully distributed queries for grid-based objects.

Latest version of open source Java In-Memory Data Grid Hazelcast supports entry processing, multi-thread execution, continuous queries and lazy indexing. They have also re-implemented all of the ...

Distributed Query Processing – Execute individual queries across many machines in a PlexQ grid for MPP, yet automatically balance workloads across the grid during peak periods Logical Servers – Group ...

A large body of work has been accomplished in distributed algorithms that is relevant in moving toward distributed query processing and query optimizers for large scale-out architectures.

Facebook has open-sourced Presto, their distributed SQL query engine. Presto uses a pipelined architecture rather than the Map/Reduce design found elsewhere. In production since early this year ...

Improve query performance 4.2 times in average compared with Apache Spark SQL which is widely used parallel query processing system in both academia and industry. Can have a huge impact on large ...

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.

Hive lets you write data queries in an SQL-like language — the Hive Query Language (HQL) — that are converted to map/reduced tasks, which are then executed by the Hadoop framework.