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 ...

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 ...

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 ...

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.

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.

Apache Flink, a distributed in-memory data processing framework project born out of Germany, this week graduated the Apache Incubator stage and became a Top-Level Project at the open source software ...