We should be able to run tests in parallel even if there is a database involved. We can leverage database transactions to keep our tests isolated from each other. There are solutions out there already ...

At the crux of many an enterprise-scale big data system stands either MapReduce or a parallel database management system. But which is more efficient? Researchers from Dublin Institute of Technology, ...

Running parallel database systems in an environment with heterogeneous resources has become increasingly common, due to cluster evolution and increasing interest in moving applications into public ...

A startup named TigerGraph emerged from stealth today with a new native parallel graph database that its founder thinks can shake up the analytics market. With $31 million in venture funding and ...

This report summarises the achievements of the EPSRC Parade project (GRJ/53348), which ran from June 1994 to September 1997. We have made contributions in the following three areas. Parallel Language ...

Data parallelism is achieved in the processEmployeesAndMetricsByDepartment function, where tasks involving querying and processing employees based on their department ...

Abstract: A database management system (DBMS) with a parallel processing database system is different from conventional database systems. Accordingly, writing SQL for a parallel processing DBMS ...

Victor Lee is director of product management at TigerGraph. Graph databases excel at answering complex questions about relationships in large data sets. But they hit a wall—in terms of both ...

Recent approaches exploiting the massively parallel architecture of graphics processors (GPUs) to accelerate database operations have achieved intriguing results. While parallel sorting received ...