Query optimisation in distributed database systems addresses the challenge of selecting an efficient execution plan across multiple networked nodes. Owing to the combinatorial explosion of possible ...
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 ...
Encrypting data is one of the most basic -- and most effective -- data security measures we have at our disposal. But when used with relational databases, encryption creates two major problems. The ...
Data intensive applications that rely heavily on huge databases waste a lot of time in searching and retrieval especially if there is a single server retrieving data from the database. This paper ...
The preprint “POLAR: Adaptive and Non-invasive Join Order Selection via Plans of Least Resistance.” introduces an adaptive query processing technique that lowers the adoption barrier for existing ...
Microsoft announced the general availability of SQL Server 2019 and SQL Server Big Data Clusters at its Ignite conference on Monday. SQL Server 2019 builds on intelligent query processing features ...
On Friday the 13th of March 2026, M.Sc. Valter Uotila defends his PhD thesis on Quantum Computing Methods for Query Optimization in Relational Databases. The thesis is related to research done in the ...
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 ...
PostgreSQL with the pgvector extension allows tables to be used as storage for vectors, each of which is saved as a row. It also allows any number of metadata columns to be added. In an enterprise ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results