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

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.

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.

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 ...

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.

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.

Oracle is taking MySQL in a new direction: introducing an aggressively priced cloud service combining transaction processing and data warehousing, with the bonus of dispensing with ETL.

Spatial data processing and query algorithms underpin a critical component of modern geospatial analysis, enabling efficient handling and interrogation of vast and complex datasets.