GRAPHITE: An Extensible Graph Traversal Framework for Relational Database Management Systems

Graph traversals are a basic but fundamental ingredient for a variety of graph algorithms and graph-oriented queries. To achieve the best possible query performance, they need to be implemented at the core of a database management system that aims at storing, manipulating, and querying graph data. Increasingly, modern business applications demand native graph query and processing capabilities for enterprise-critical operations on data stored in relational database management systems. In this paper we propose an extensible graph traversal framework (GRAPHITE) as a central graph processing component on a common storage engine inside a relational database management system. We study the influence of the graph topology on the execution time of graph traversals and derive two traversal algorithm implementations specialized for different graph topologies and traversal queries. We conduct extensive experiments on GRAPHITE for a large variety of real-world graph data sets and input configurations. Our experiments show that the proposed traversal algorithms differ by up to two orders of magnitude for different input configurations and therefore demonstrate the need for a versatile framework to efficiently process graph traversals on a wide range of different graph topologies and types of queries. Finally, we highlight that the query performance of our traversal implementations is competitive with those of two native graph database management systems

Information Exchange Between Humanitarian Organizations: Using the XML Schema IDML

This article explains challenges that arise when humanitarian organizations want to coordinate their development activities by means of distributed information systems. It focuses on information exchange based on the eXtensible Markup Language (XML) and relational databases. This piece discusses how to save hierarchical XML documents in relational databases. It introduces conversion rules to derive a relational database model from XML schemas. The rules are applied for the design of a database for the management of humanitarian development projects. The underlying schema for the database is the International Development Markup Language (IDML). This exchange standard for development-related activities is described. The article gives details on how a traditional relational database can import or export XML documents, i.e. how it can be XML-enabled

bdbms -- A Database Management System for Biological Data

Biologists are increasingly using databases for storing and managing their data. Biological databases typically consist of a mixture of raw data, metadata, sequences, annotations, and related data obtained from various sources. Current database technology lacks several functionalities that are needed by biological databases. In this paper, we introduce bdbms, an extensible prototype database management system for supporting biological data. bdbms extends the functionalities of current DBMSs to include: (1) Annotation and provenance management including storage, indexing, manipulation, and querying of annotation and provenance as first class objects in bdbms, (2) Local dependency tracking to track the dependencies and derivations among data items, (3) Update authorization to support data curation via content-based authorization, in contrast to identity-based authorization, and (4) New access methods and their supporting operators that support pattern matching on various types of compressed biological data types. This paper presents the design of bdbms along with the techniques proposed to support these functionalities including an extension to SQL. We also outline some open issues in building bdbms.Comment: This article is published under a Creative Commons License Agreement (http://creativecommons.org/licenses/by/2.5/.) You may copy, distribute, display, and perform the work, make derivative works and make commercial use of the work, but, you must attribute the work to the author and CIDR 2007. 3rd Biennial Conference on Innovative Data Systems Research (CIDR) January 710, 2007, Asilomar, California, US

FMKe: A realistic benchmark for key-value stores

Standard benchmarks are essential tools to evaluate and compare database management systems in terms of relevant semantic properties and performance. They provide the means to evaluate a system with workloads that mimic real applications. Although a number of realistic benchmarks already exist for relational database systems, the same cannot be said for NoSQL databases. This latter class of data storage systems has become increasingly relevant for geo-distributed systems, and this has led developers and researchers to either rely on benchmarks that do not model realistic workloads or to adapt the aforementioned benchmarks for relational databases to work for NoSQL databases, in a somewhat ad-hoc fashion. Since these benchmarks assume an isolation and transactional model in the database, they are inherently inadequate to evaluate NoSQL databases. In this thesis, we propose a new benchmark that addresses the lack of realistic evaluation tools for distributed key-value stores. We consider a workload that is based on information we have acquired about a real world deployment of a large-scale application that operates over a distributed key-value store, that is responsible for managing patient prescriptions at a nation-wide level in Denmark. We design our benchmark to be extensible to a wide range of distributed key-value storage systems and some relational database systems with minimal effort for programmers, which only need to design and implement specific data storage drivers to benchmark different alternatives. We further present a study on the performance of multiple database management systems in different deployment scenarios