Users have the ability to consume both multidimensional (OLAP) and relational data with SQL Server 2005 Reporting Services technology and the Report Builder feature. Learn how you can use this feature ...

Over the last couple of decades, large multi-dimensional databases have become ubiquitous in a vast array of application areas, such as corporate data warehouses as well as projects in scientific ...

A multidimensional database is a variation of the relational model that uses multidimensional structures to organize data and express the relationships between data. [2] Multidimensional databases are ...

Over the last couple of decades, large multi-dimensional databases have become ubiquitous in a vast array of application areas, such as corporate data warehouses as well as projects in scientific ...

Excerpt from Microsoft SQL Server 2008 Analysis Services Unleashed by Irina Gorbach, Alexander Berger, Edward Melomed Chapter 1: Introduction to OLAP and Its Role in Business Intelligence Excerpt from ...

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 ...

In “The end of SQL and relational databases? (part 1 of 3)” I covered some background on the SQL language and relational databases, the current and future for relational databases, the rise of ...

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 ...

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 ...

Learn the key differences between relational and NoSQL databases with this in-depth comparison. There’s nothing wrong with the traditional relational database management system. In fact, many NoSQL ...