Moa: extensibility and efficiency in querying nested data

Abstract

Advanced non-traditional application domains such as geographic information systems and digital library systems demand advanced data management support. In an effort to cope with this demand, we present a novel multi-model DBMS architecture which provides efficient evaluation of queries on complexly structured data. A vital role in this architecture is played by the Moa language featuring a nested relational data model based on XNF2, in which we placed renewed interest. Furthermore, the architecture allows extensibility on all of its levels providing the means to better integrate domain-specific algorithms into the system. In addition to this, the extensibility of the Moa language is designed in a way that optimization obstacles due to blackbox treatment of ADTs is avoided. This combination of well-integrated domainspecific algorithms, extensibility open to optimization, and a mapping of queries on complexly structured data to an efficient physical algebra expression via a nested relational algebra, makes that the Moa system can efficiently handle complex queries from non-traditional application domains