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 ...

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 ...

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 ...

Many programs have a tough time spanning across high levels of concurrency, but if they are cleverly coded, databases can make great use of massively parallel compute based in hardware to radically ...

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 ...

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 ...

Overview: SQLite is suitable for apps that require reliable storage and small but frequent updates.DuckDB can handle large ...