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, ...

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 ...

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 ...

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 ...

Traditionally data acquisition has been the bottleneck for large scale proteomics. This has also remained one of the limitations in leveraging mass spectrometry within the clinic. PASEF and short ...

Graph databases, which explicitly express the connections between nodes, are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. That ...

Hardware accelerated databases are not new things. More than twenty years ago, Netezza was founded and created a hybrid hardware architecture that ran PostgreSQL on a big, wonking NUMA server running ...

The tide is changing for analytics architectures. Traditional approaches, from the data warehouse to the data lake, implicitly assume that all relevant data can be stored in a single, centralized ...