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 ...

The rapid expansion of data volumes in modern applications has intensified the need for efficient methods of storing and retrieving information. Contemporary research in data compression focuses on ...

The expanding volume and complexity of modern datasets have necessitated innovative approaches to data query processing and visualisation. Contemporary methods must efficiently extract actionable ...

Online analytical processing (OLAP) databases are purpose-built for handling analytical queries. Analytical queries run on online transaction-processing (OLTP) databases often take a long time to ...

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 ...

What is good for the simulation and the machine learning is, as it turns out, also good for the database. The performance and thermal limits of traditional CPUs have made GPUs the go-to accelerator ...

A new generation of graph databases has taken hold, and a generation of query languages has arrived alongside them. The assorted graph database query languages include the likes of Gremlin, Cypher, ...