The Cisco Data Fabric and Splunk Federated Search for Snowflake will enable enterprises to unify, analyze, and gain insights ...

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 ...

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.

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.

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.

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.

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.

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.