One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the ...

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 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 relational database is a set of formally described tables from which data can be accessed or reassembled in many different ways without having to reorganize the database tables. The standard user ...

Every day, businesses depend on data to operate. Customer orders, quotes for new business, conversations around products, campaigns for marketing—pretty much every business process today is based on ...

In the beginning, there were files. Later there were navigational databases based on structured files. Then there were IMS and CODASYL, and around 40 years ago we had some of the first relational ...

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 ...

Even with all the hype around NoSQL, traditional relational databases still make sense for enterprise applications. Here are four reasons why. Dave Rosenberg Co-founder, MuleSource Dave Rosenberg has ...

Analysts say Redmond still has billions of reasons to keep backing its flagship DBMS, even as Azure, Postgres, and AI hog the ...