SQL Server 2019 builds on intelligent query processing features that were implemented in SQL Server 2017, and expands them to new areas of the database engine. Let's take a deeper dive into some ...

Prior to SQL Server 2017, query processing was a monolithic process. The SQL Server query optimizer would first construct a query plan for a batch of T-SQL code, a stored procedure, or function and ...

Spark SQL: Apache’s Spark project is for real-time, in-memory, parallelized processing of Hadoop data.Spark SQL builds on top of it to allow SQL queries to be written against data. A better way ...

The next version of Microsoft’s relational database management system (RDMS) promises to bring immense performance gains to online transactional processing systems. SQL Server 2014 will come ...

The next version of Microsoft’s relational database management system (RDMS) promises to bring immense performance gains to online transactional processing systems. SQL Server 2014 will come ...

With Teradata QueryGrid, your data warehouse can now intelligently use the functionality of multiple, heterogeneous processing engines, including Hadoop.

On a 1 billion row dataset, Mostak says that MapD can process SQL queries in around 10 milliseconds to 20 milliseconds. The data ingest for the system is very fast, too, which is important. Ahead of ...

Query processing and optimisation are critical components of modern database systems, ... A survey on deep learning approaches for text-to-SQL. The VLDB Journal (2023).

Object storage is winning the battle for big data storage in such a convincing fashion that database makers are beginning to cede data storage to object storage vendors and concentrating instead on ...