Auflistung nach Autor:in "Kersten, Martin"
1 - 3 von 3
Treffer pro Seite
Sortieroptionen
- KonferenzbeitragArmada: a Reference Model for an Evolving Database System(Datenbanksysteme in Business, Technologie und Web (BTW 2007) – 12. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS), 2007) Groffen, Fabian; Kersten, Martin; Manegold, StefanThe data on the web, in digital libraries, in scientific repositories, etc. con- tinues to grow at an increasing rate. Distribution is a key solution to overcome this data explosion. However, existing solutions are mostly based on architectures with a single point of failure. In this paper, we present Armada, a model for a database architecture to handle large data volumes. Armada assumes autonomy of sites, allowing for a decentralised setup, where systems can largely work independently. Furthermore, a novel administration schema in Armada, based on lineage trails, allows for flexible adaptation to the (query) work load in highly dynamic environments. The lineage trails capture the metadata and its history. They form the basis to direct updates to the proper sites, to break queries into multi-stage plans, and to provide a reference point for site consistency. The lineage trails are managed in a purely distributed fashion, each Armada site is responsible for their persistency and long term availability. They provide a minimal, but sufficient basis to handle all distributed query processing tasks. The analysis of the Armada reference architecture depicts a path for innovative research at many levels of a DBMS. Challenging many conventional database assumptions and theories, it will eventually allow large databases to continue to grow and stay flexible.
- ZeitschriftenartikelGenome sequence analysis with MonetDB(Datenbank-Spektrum: Vol. 15, No. 3, 2015) Cijvat, Robin; Manegold, Stefan; Kersten, Martin; Klau, Gunnar W.; Schönhuth, Alexander; Marschall, Tobias; Zhang, YingNext-generation sequencing (NGS) technology has led the life sciences into the big data era. Today, sequencing genomes takes little time and cost, but yields terabytes of data to be stored and analyzed. Biologists are often exposed to excessively time consuming and error-prone data management and analysis hurdles. In this paper, we propose a database management system (DBMS) based approach to accelerate and substantially simplify genome sequence analysis. We have extended MonetDB, an open-source column-based DBMS, with a BAM module, which enables easy, flexible, and rapid management and analysis of sequence alignment data stored as Sequence Alignment/Map (SAM/BAM) files. We describe the main features of MonetDB/BAM using a case study on Ebola virusgenomes.
- KonferenzbeitragGenome sequence analysis with monetdb: a case study on ebola virus diversity(Datenbanksysteme für Business, Technologie und Web (BTW 2015) - Workshopband, 2015) Cijvat, Robin; Manegold, Stefan; Kersten, Martin; Klau, Gunnar W.; Schönhuth, Alexander; Marschall, Tobias; Zhang, YingNext-generation sequencing (NGS) technology has led the life sciences into the big data era. Today, sequencing genomes takes little time and cost, but results in terabytes of data to be stored and analysed. Biologists are often exposed to excessively time consuming and error-prone data management and analysis hurdles. In this paper, we propose a database management system (DBMS) based approach to accelerate and substantially simplify genome sequence analysis. We have extended MonetDB, an open-source column-based DBMS, with a BAM module, which enables easy, flexible, and rapid management and analysis of sequence alignment data stored as Sequence Alignment/Map (SAM/BAM) files. We describe the main features of MonetDB/BAM using a case study on Ebola virus genomes.