An introduction to Graph Data Management

A graph database is a database where the data structures for the schema and/or instances are modeled as a (labeled)(directed) graph or generalizations of it, and where querying is expressed by graph-oriented operations and type constructors. In this article we present the basic notions of graph databases, give an historical overview of its main development, and study the main current systems that implement them

Heuristic optimization of OLAP queries in multidimensionally hierarchically clustered databases

On-Line Analytical Processing (OLAP) is a technology that encompasses applications requiring a multidimen-sional and hierarchical view of data. OLAP applica-tions often require fast response time to complex group-ing/aggregation queries on enormous quantities of data. Commercial relational database management systems use mainly multiple one-dimensional indexes to process OLAP queries that restrict multiple dimensions. How-ever, in many cases, multidimensional access methods outperform one-dimensional indexing methods. We present an architecture for multidimensional data-bases that are clustered with respect to multiple hi-erarchical dimensions. It is based on the star schema and is called CSB star. Then, we focus on heuristi-cally optimizing OLAP queries over this schema using multidimensional access methods. Users can still formu-late their queries over a traditional star schema, which are then rewritten by the query processor over the CSB star. We exploit the different clustering features of the CSB star to efficiently process a class of typical OLAP queries. We detect special cases where the construction of an evaluation plan can be simplified and we discuss improvements of our technique. 1