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 ...

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 ...

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 ...

Data is only going to continue to grow and with that, so must data processing capabilities. Many of the more traditional methods of data processing have struggled to keep with the immense surge in ...

The three features of adaptive query processing can make SQL Server 2017 significantly faster at processing your workload. Not only that, but they also provide significant improvements without needing ...

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, ...

NoSQL databases arose in response to the limitations of using SQL (Structured Query Language) for database queries. NoSQL databases store and manage data in ways that enable high operational speed and ...