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 ...

Raph Koster couldn't help but wonder when he read the blog post entitled, "Lessons Learned: Sharding for startups," if he had a hand in creating that terminology. Sharding, as this blog post put it, ...

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 ...

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 ...

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 ...

SAN DIEGO, Sept. 18, 2013 /PRNewswire/ — Teradata (NYSE: TDC), the leading analytic data solutions company, announced it is the first to offer next-generation, in-database R Analytics that are fully ...

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 ...

To avoid database conflicts that may occur when different test cases in different parallel threads attempt to access the same database simultaneously, testing of the software application can be ...