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 ...

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, ...

In this video from FOSDEM 2020, Frank McQuillan from Pivotal presents: Efficient Model Selection for Deep Neural Networks on Massively Parallel Processing Databases. In this session we will present an ...

Abstract: In present scenario parallel database systems are being applicable in a broad range of systems, right from database applications (OLTP) server to decision support systems (OLAP) server.

This project aims to accelerate database query execution using a hybrid parallel approach, combining CPU-based parallelism (OpenMP) and GPU-based acceleration (CUDA). The expected outcome is a ...

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

Maybe, if you need blazing performance extracting data and chewing on it from a relational database, it belongs in a cloud. Because for certain workloads, including vector search and retrieval ...

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