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.

Query processing and optimisation are critical components of modern database systems, serving to translate high‐level declarative queries into efficient, low‐level machine instructions. At its ...

Distributed query processing: a query—or request to read large data sets—enters at a client level and is processed and optimized on the global level.

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 ...

Apache Pinot is an open-source, distributed database for customer-facing, real-time analytics, ingesting data from various sources and executing queries using SQL. It is implemented in Java.

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 ...

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.

Facebook has open sourced Presto, its distributed SQL query engine built to improve Big Data analytics beyond existing solutions such as Hadoop MapReduce and Hive.