Recent advances in graphics processing units (GPUs) have opened a new frontier in query processing and database systems. Leveraging the massively parallel architecture of GPUs, modern database engines ...

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 ...

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 ...

For many years, and quite a long time ago in computer time, Hadoop was seen as the best way to store and analyze mountains of unstructured data. But then workloads and data began shifting to the ...

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, ...