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 ...

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 ...

Yale University researchers on Monday released an open-source parallel database that they say combines the data-crunching prowess of a relational database with the scalability of next-generation ...

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 ...

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 ...

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 ...

Early scaling decisions can come back to haunt you. Follow these tips to ensure that data sharding actually helps, rather than hinders, the scalability of your application. New SaaS startups rarely ...