A database that maintains a set of separate, related files (tables), but combines data elements from the files for queries and reports when required. The concept was developed in 1970 by Edgar Codd, ...

Relational database management systems (RDBMS) rely on an optimizer (or relational optimizer) that transforms SQL statements into executable code. Before any SQL statement can be run by the RDBMS, the ...

Most database startups avoid building relational databases, since that market is dominated by a few goliaths. Oracle, MySQL and Microsoft SQL Server have embedded themselves into the technical fabric ...

For over two decades, Oracle, IBM, and Microsoft relational databases were the only consistent leaders in the Gartner Magic Quadrant for Operational Database Management Systems--and there were few ...

NoSQL keeps rising, but relational databases still dominate big data Your email has been sent NoSQL promised to upend the database market as big data forced a sea change in how we think about and ...

Relational SQL databases, which have been around since the 1980s, historically ran on mainframes or single servers—that’s all we had. If you wanted the database to handle more data and run faster, you ...

A question asked about data contained in two or more tables in a relational database. The relational query must specify the tables required and what the condition is that links them; for example, ...

File-based databases have been around since the dawn of computing. We’ve always needed to have a way of storing records of the same kind of information. In the PC world, we ended up with very popular ...

Data integration can seem like a never-ending quest as organizations try to combine and access data from disparate applications and sources. But as we move beyond relational as the only DBMS type that ...

Conventional wisdom states that relational databases are not scalable or robust enough to handle the huge numbers of connections, the massive throughput, and all the cool tricks required to master IoT ...