By realigning data access patterns and utilising idle SIMD lanes, these algorithms have achieved performance boosts in critical operations such as table scans, hash joins, and geospatial queries [3].

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 ...

With POLAR, the research group introduces an adaptive query processing technique that lowers the adoption barrier for existing database systems while decreasing the risk of performance cliffs from ...

“The database market is so competitive at this point that they all want to focus on query optimization,” he continues. “They all want to deliver high performance querying, and they all want to do it ...

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 ...

This helps streamline query processing work. Multiple data transfers from disks are also eliminated, as are multiple data copies in memory, and CPU demands are minimized.

In Kinetica, vectorization is made possible due to the combined use of graphical processing units (GPUs) and CPUs, the company said, adding that the database uses SQL-92 for a query language, just ...

Blockchain can be inefficient in terms of data processing and query performance. Source: MDPI Another reason data queries are inefficient is the linear storage of data in blockchain networks.

Quicker query processing, in turn, improves the performance of analytics workloads. The database also includes other performance optimizations.