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 ...

AWS has announced Parallel Query for Amazon Aurora. According to the company, this provides faster analytical queries over transactional data that can speed up queries by up to 2 orders of magnitude, ...

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 ...

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 ...

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 ...

To survive in today's ultra-competitive business environment, companies have to be adaptable and be able to move quickly with the ever-changing market conditions. It's not enough to simply have a good ...

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 ...

There is an arms race in the nascent market for GPU-accelerated databases, and the winner will be the one that can scale to the largest datasets while also providing the most compatibility with ...

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, ...