thereby successfully resolving critical issues in database partitioning method and parallel and distributed query processing technologies. GPT technology uses graph-theoretic view for modeling co ...

In these architectures, data is distributed across several specialized data stores such as data warehouses, Hadoop clusters, and cloud databases ... the network before the parallel processing even ...

This paper proposes a Beowulf cluster for fast query processing by distributing the database horizontally over nodes through a load balancing act. A mathematical model is proposed to optimally ...

Many organizations do not have the talent at their disposal to deal in complex MapReduce queries. Also, parallel DBMS sports a better capability for repeated structured data processing. Once a large ...

Online analytical processing (OLAP) databases are purpose-built for handling analytical queries. Analytical queries ... and/or by using many CPUs in parallel (i.e., massively parallel processing ...

MariaDB, originally best known as a fork of the open source MySQL database ... now provides: distributed scale-out capabilities; columnar storage/massively parallel processing (MPP) data warehouse ...

a real-time analytics database that has surpassed Hadoop’s analysis capabilities. The difference is in its parallel-computing capabilities and SQL-like functionality. Do a query across petabytes ...

Sybase has changed the structure of its Sybase IQ column-based database software to allow queries to be run in parallel ... which means they are distributed across multiple separate processors.