DOCSLIB.ORG

Enterprise Information Integration: Successes, Challenges and Controversies

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Enterprise Information Integration: Successes, Challenges and Controversies Enterprise Information Integration: Successes, Challenges and Controversies Alon Y. Halevy∗(Editor), Naveen Ashish,y Dina Bitton,z Michael Carey,x Denise Draper,{ Jeff Pollock,k Arnon Rosenthal,∗∗Vishal Sikkayy ABSTRACT Several factors came together at the time to contribute to The goal of EII Systems is to provide uniform access to the development of the EII industry. First, some technolo- multiple data sources without having to first loading them gies developed in the research arena have matured to the into a data warehouse. Since the late 1990's, several EII point that they were ready for commercialization, and sev- products have appeared in the marketplace and significant eral of the teams responsible for these developments started experience has been accumulated from fielding such systems. companies (or spun off products from research labs). Sec- This collection of articles, by individuals who were involved ond, the needs of data management in organizations have in this industry in various ways, describes some of these changed: the need to create external coherent web sites experiences and points to the challenges ahead. required integrating data from multiple sources; the web- connected world raised the urgency for companies to start communicating with others in various ways. Third, the 1. INTRODUCTORY REMARKS emergence of XML piqued the appetites of people to share data. Finally, there was a general atmosphere in the late 90's Alon Halevy that any idea is worth a try (even good ones!). Importantly, University of Washington & Transformic Inc. data warehousing solutions were deemed inappropriate for [email protected] supporting these needs, and the cost of ad-hoc solutions were beginning to become unaffordable. Broadly speaking, the architectures underlying the prod- Beginning in the late 1990's, we have been witnessing the ucts were based on similar principles. A data integration budding of a new industry: Enterprise Information Integra- scenario started with identifying the data sources that will tion (EII). The vision underlying this industry is to provide participate in the application, and then building a virtual tools for integrating data from multiple sources without hav- schema (often called a mediated schema), which would be ing to first load all the data into a central warehouse. In the queried by users or applications. Query processing would be- research community we have been referring to these as data gin by reformulating a query posed over the virtual schema integration systems. into queries over the data sources, and then executing it effi- This collection of articles accompanies a session at the ciently with an engine that created plans that span multiple SIGMOD 2005 Conference in which the authors discuss the data sources and dealt with the limitations and capabilities successes of the EII industry, the challenges that lie ahead of each source. Some of the companies coincided with the of it and the controversies surrounding it. The following few emergence of XML, and built their systems on an XML data paragraphs serve as an introduction to the issues, admittedly model and query language (XQuery was just starting to be with the perspective of the editor. developed at the time). These companies had to address ∗University of Washington double the problems of the other companies, because the re- yNasa Ames search on efficient query processing and integration for XML zCallixa was only in its infancy, and hence they did not have a vast xBEA Systems literature to draw on. {Microsoft Corporation Some of the first applications in which these systems were kNetwork Inference fielded successfully were customer-relationship management, ∗∗Mitre Corporation where the challenge was to provide the customer-facing worker yySAP a global view of a customer whose data is residing in mul- tiple sources, and digital dashboards that required tracking information from multiple sources in real time. As with any new industry, EII has faced many challenges, Permission to make digital or hard copies of all or part of this work for some of which still impede its growth today. The following personal or classroom use is granted without fee provided that copies are are representative ones: not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to Scaleup and performance: The initial challenge was to republish, to post on servers or to redistribute to lists, requires prior specific convince customers that the idea would work. How could permission and/or a fee. SIGACM­SIGMOD '05 Baltimore, Maryland USA a query processor that accesses the data sources in real Copyright 200X ACM X­XXXXX­XX­X/XX/XX ...$5.00. time have a chance of providing adequate and predictable performance? In many cases, administrators of (very care- tential, and its positioning still needs to be further refined. fully tuned) data sources would not even consider allowing I personally believe that the success of the industry will de- a query from an external query engine to hit them. In this pend to a large extent on delivering useful tools at the higher context EII tools often faced competition from the relatively levels of the information food chain, namely for meta-data mature data warehousing tools. To complicate matters, the management and schema heterogeneity. warehousing tools started emphasizing their real-time capa- bilities, supposedly removing one of the key advantages of 2. TOWARDS COST­EFFECTIVE AND SCAL­ EII over warehousing. The challenge was to explain to po- tential customers the tradeoffs between the cost of building ABLE INFORMATION INTEGRATION a warehouse, the cost of a live query and the cost of ac- cessing stale data. Customers want simple formulas they Naveen Ashish could apply to make their buying decisions, but those are NASA Ames not available. [email protected] Horizontal vs. Vertical growth: From a business per- EII is an area that I have had involvement with for the spective, an EII company had to decide whether to build past several years. I am currently a researcher at NASA a horizontal platform that can be used in any application Ames Research Center, where data integration has been and or to build special tools for a particular vertical. The ar- remains one of my primary research and technical interests. gument for the vertical approach was that customers care At NASA I have been involved in both developing infor- about solving their entire problem, rather than paying for mation integration systems in various domains, as well as yet another piece of the solution and having to worry about developing applications for specific mission driven applica- how it integrates with other pieces. The argument for the tions of use to NASA. The domains have included integra- horizontal approach is the generality of the system and of- tion of enterprise information, and integration of aviation ten the inability to decide (in time) which vertical to focus safety related data sources. Previously I was a co-developer on. The problem boiled down to how to prioritize the scarce for some of the core technologies for Fetch Technologies, an resources of a startup company. information extraction and integration company spun out of my research group at USC/ISI in 2000. My work at NASA Integration with EAI tools and other middleware: has provided the opportunity to look at EII not only from To put things mildly, the space of data management mid- a developer and provider perspective, but also from a con- dleware products is a very complicated one. Different com- sumer perspective in terms of applying EII to the NASA panies come at related problems from different perspectives enterprise's information management needs. and it's often difficult to see exactly which part of the prob- A primary concern for EII today regards the scalability lem a tool is solving. The emergence of EII tools only further and economic aspects of data integration. The need for complicated the problem. A slightly more mature sector middleware and integration technology is inevitable, more so is EAI (Enterprise Application Integration) whose products with the shifting computing paradigms as noted in [10]. Our try to facilitate hooking up applications to talk to each other experience with enterprise data integration applications in and thereby support certain workflows. Whereas EAI tends the NASA enterprise tells us that traditional schema-centric to focus on arbitrary applications, EII focuses on the data mediation approaches to data integration problems are of- and querying it. However, at some point, data needs to be ten overkill and lead to overly and unnecessary investment fed into applications, and their output feeds into other data in terms of time, resources and cost. In fact the investment sources. In fact, to query the data one can use an EII tool, in schema management per new source integrated and in but to update the data one typically has to resort to an heavy-weight middleware are reasons why user costs increase EAI tool. Hence, the separation between EII and EAI tools directly (linearly) with the user benefit with the primary in- may be a temporary one. Other related products include vestment going to the middleware IT product and service data cleaning tools and reporting and analysis tools, whose providers. What is beneficial to end users however are in- integration with EII and EAI does stand to see significant tegration technologies that truly demonstrate economies of improvement. scale, with costs of adding newer sources decreasing signifi- Meta-data Management and Semantic Heterogene- cantly as the total number of sources integrated increases. ity: One of the key issues faced in data integration projects How is scalability and cost-effectiveness in data integra- is locating and understanding the data to be integrated.
Load more

Recommended publications
  • Preview MS Access Tutorial (PDF Version)
    MS Access About the Tutorial Microsoft Access is a Database Management System (DBMS) from Microsoft that combines the relational Microsoft Jet Database Engine with a graphical user interface and software- development tools. It is a part of the Microsoft Office suite of applications, included in the professional and higher editions. This is an introductory tutorial that covers the basics of MS Access. Audience This tutorial is designed for those people who want to learn how to start working with Microsoft Access. After completing this tutorial, you will have a better understating of MS Access and how you can use it to store and retrieve data. Prerequisites It is a simple and easy-to-understand tutorial. There are no set prerequisites as such, and it should be useful for any beginner who want acquire knowledge on MS Access. However it will definitely help if you are aware of some basic concepts of a database, especially RDBMS concepts. Copyright and Disclaimer Copyright 2018 by Tutorials Point (I) Pvt. Ltd. All the content and graphics published in this e-book are the property of Tutorials Point (I) Pvt. Ltd. The user of this e-book is prohibited to reuse, retain, copy, distribute or republish any contents or a part of contents of this e-book in any manner without written consent of the publisher. We strive to update the contents of our website and tutorials as timely and as precisely as possible, however, the contents may contain inaccuracies or errors. Tutorials Point (I) Pvt. Ltd. provides no guarantee regarding the accuracy, timeliness or completeness of our website or its contents including this tutorial.
    [Show full text]
  • Managing Data in Motion This Page Intentionally Left Blank Managing Data in Motion Data Integration Best Practice Techniques and Technologies
    Managing Data in Motion This page intentionally left blank Managing Data in Motion Data Integration Best Practice Techniques and Technologies April Reeve AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Morgan Kaufmann is an imprint of Elsevier Acquiring Editor: Andrea Dierna Development Editor: Heather Scherer Project Manager: Mohanambal Natarajan Designer: Russell Purdy Morgan Kaufmann is an imprint of Elsevier 225 Wyman Street, Waltham, MA 02451, USA Copyright r 2013 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods or professional practices, may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information or methods described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility.
    [Show full text]
  • Declarative Access to Filesystem Data New Application Domains for XML Database Management Systems
    Declarative Access to Filesystem Data New application domains for XML database management systems Alexander Holupirek Dissertation zur Erlangung des akademischen Grades Doktor der Naturwissenschaften (Dr. rer. nat.) Fachbereich Informatik und Informationswissenschaft Mathematisch-Naturwissenschaftliche Sektion Universität Konstanz Referenten: Prof. Dr. Marc H. Scholl Prof. Dr. Marcel Waldvogel Tag der mündlichen Prüfung: 17. Juli 2012 Abstract XML and state-of-the-art XML database management systems (XML-DBMSs) can play a leading role in far more application domains as it is currently the case. Even in their basic configuration, they entail all components necessary to act as central systems for complex search and retrieval tasks. They provide language-specific index- ing of full-text documents and can store structured, semi-structured and binary data. Besides, they offer a great variety of standardized languages (XQuery, XSLT, XQuery Full Text, etc.) to develop applications inside a pure XML technology stack. Benefits are obvious: Data, logic, and presentation tiers can operate on a single data model, and no conversions have to be applied when switching in between. This thesis deals with the design and development of XML/XQuery driven informa- tion architectures that process formerly heterogeneous data sources in a standardized and uniform manner. Filesystems and their vast amounts of different file types are a prime example for such a heterogeneous dataspace. A new XML dialect, the Filesystem Markup Language (FSML), is introduced to construct a database view of the filesystem and its contents. FSML provides a uniform view on the filesystem’s contents and allows developers to leverage the complete XML technology stack on filesystem data.
    [Show full text]
  • Plataforma De Datos Virtuoso
    Plataforma de Datos Virtuoso: Arquitectura, Tecnologías y Caso de Estudio Virtuoso Data Platform: Architecture, Technology and Case Study Andrés Nacimiento García Dpto. Ingeniería Informática Escuela Técnica Superior de Ingeniería Informática Trabajo de Fin de Grado La Laguna, 27 de febrero de 2015 Dña. Elena Sánchez Nielsen, profesora de Universidad adscrita al Departamento de Ingeniería Informática de la Universidad de La Laguna C E R T I F I C A Que la presente memoria titulada: “Plataforma de Datos Virtuoso: Arquitectura, Tecnologías y Caso de Estudio.” ha sido realizada bajo su dirección por D. Andrés Nacimiento García. Y para que así conste, en cumplimiento de la legislación vigente y a los efectos oportunos firman la presente en La Laguna a 27 de febrero de 2015. Agradecimientos Agradecimiento especial a Jésica por su apoyo incondicional. A Mª de los Ángeles por sus conocimientos en inglés. A mi familia por el apoyo recibido. A la directora del proyecto por su tiempo y paciencia. Al soporte técnico de OpenLink Virtuoso por ofrecerse personalmente en caso de tener algún problema. A toda esa gente anónima que aporta documentación en internet para que proyectos como éste se puedan llevar a cabo. Resumen El presente trabajo fin de grado tiene como finalidad el estudio y análisis de las funcionalidades y prestaciones de la plataforma de datos Virtuoso en el manejo de datos relacionales y RDF, así como en el desarrollo de aplicaciones Web para acceder a dichos datos. Con esta finalidad, este trabajo fin de grado, se divide en dos partes. Una primera parte, que se focaliza sobre el estudio y análisis de las funcionalidades de la plataforma Virtuoso.
    [Show full text]
  • What's New in Pervasive PSQL Is Divided Into the Following Sections
    Pervasive PSQL v10 SP2 What’s New in Pervasive PSQL An Overview of New Features and Changed Behavior Pervasive Software Inc. 12365 Riata Trace Parkway Building B Austin, TX 78727 USA Telephone: 512 231 6000 or 800 287 4383 Fax: 512 231 6010 Email: [email protected] Web: http://www.pervasive.com disclaimer PERVASIVE SOFTWARE INC. LICENSES THE SOFTWARE AND DOCUMENTATION PRODUCT TO YOU OR YOUR COMPANY SOLELY ON AN “AS IS” BASIS AND SOLELY IN ACCORDANCE WITH THE TERMS AND CONDITIONS OF THE ACCOMPANYING LICENSE AGREEMENT. PERVASIVE SOFTWARE INC. MAKES NO OTHER WARRANTIES WHATSOEVER, EITHER EXPRESS OR IMPLIED, REGARDING THE SOFTWARE OR THE CONTENT OF THE DOCUMENTATION; PERVASIVE SOFTWARE INC. HEREBY EXPRESSLY STATES AND YOU OR YOUR COMPANY ACKNOWLEDGES THAT PERVASIVE SOFTWARE INC. DOES NOT MAKE ANY WARRANTIES, INCLUDING, FOR EXAMPLE, WITH RESPECT TO MERCHANTABILITY, TITLE, OR FITNESS FOR ANY PARTICULAR PURPOSE OR ARISING FROM COURSE OF DEALING OR USAGE OF TRADE, AMONG OTHERS. trademarks Btrieve, Client/Server in a Box, Pervasive, Pervasive Software, and the Pervasive Software logo are registered trademarks of Pervasive Software Inc. Built on Pervasive Software, DataExchange, MicroKernel Database Engine, MicroKernel Database Architecture, Pervasive.SQL, Pervasive PSQL, Solution Network, Ultralight, and ZDBA are trademarks of Pervasive Software Inc. Microsoft, MS-DOS, Windows, Windows 95, Windows 98, Windows NT, Windows Millennium, Windows 2000, Windows XP, Win32, Win32s, and Visual Basic are registered trademarks of Microsoft Corporation. NetWare and Novell are registered trademarks of Novell, Inc. NetWare Loadable Module, NLM, Novell DOS, Transaction Tracking System, and TTS are trademarks of Novell, Inc. Sun, Sun Microsystems, Java, all trademarks and logos that contain Sun, Solaris, or Java, are trademarks or registered trademarks of Sun Microsystems.
    [Show full text]
  • Xquery Reloaded
    XQuery Reloaded Roger Bamford3 Vinayak Borkar5 Matthias Brantner2 Peter M. Fischer4 Daniela Florescu3 David Graf2 Donald Kossmann2;4 Tim Kraska4 Dan Muresan1 Sorin Nasoi1 Markos Zacharioudakis3 1FLWOR Foundation 228msec, Inc. 3Oracle Corp. www.flworfound.org www.28msec.com www.oracle.com 4Systems Group, ETH Zurich 5University of California, Irvine www.systems.ethz.ch www.cs.uci.edu Contact: contact@flworfound.org ABSTRACT try and academia. At the beginning of this decade, XML and, This paper describes a number of XQuery-related projects. Its goal as a consequence, XQuery, was a hot topic at the major database is to show that XQuery is a useful tool for many different applica- conferences (SIGMOD and VLDB). Furthermore, all the major tion scenarios. In particular, this paper tries to correct a common database vendors integrated XQuery into their database products myth that XQuery is merely a query language and that SQL is the and made XQuery, like SQL, one possible way to extract data from better query language. Instead, XQuery is a full-fledged program- a database. Based on user feedback, Oracle has at least 7000 cus- ming language for Web applications and services. Furthermore, tomers using this feature. this paper tries to correct a second myth that XQuery is slow. This Arguably, XQuery has been most successful in the middle-tier. paper gives an overview of the state-of-the-art in XQuery imple- In the middle-tier, XQuery can serve several purposes. One promi- mentation and optimization techniques and discusses one particu- nent example is the transformation and routing of XML messages lar open-source XQuery processor, Zorba, in more detail.
    [Show full text]
  • NET Data Access Architecture Guide Information in This Document, Including URL and Other Internet Web Site References, Is Subject to Change Without Notice
    .NET Data Access Architecture Guide Information in this document, including URL and other Internet Web site references, is subject to change without notice. Unless otherwise noted, the example companies, organizations, products, domain names, e-mail addresses, logos, people, places and events depicted herein are fictitious, and no association with any real company, organization, product, domain name, e-mail address, logo, person, place or event is intended or should be inferred. Complying with all applicable copyright laws is the responsibility of the user. Without limiting the rights under copyright, no part of this document may be reproduced, stored in or introduced into a retrieval system, or transmitted in any form or by any means (electronic, mechanical, photocopying, recording, or otherwise), or for any purpose, without the express written permission of Microsoft Corporation. Microsoft, ActiveX, Microsoft Press, Visual Basic, Visual Studio, and Windows are either registered trademarks or trademarks of Microsoft Corporation in the United States and/or other countries. © 2003 Microsoft Corporation. All rights reserved. Version 1.0 The names of actual companies and products mentioned herein may be the trademarks of their respective owners. Contents .NET Data Access Architecture Guide Introduction . 1 Who Should Read This Document . 2 What You Must Know . 2 What’s New . 2 Introducing ADO.NET . 2 .NET Data Providers . 5 Stored Procedures vs. Direct SQL . 8 Properties vs. Constructor Arguments . 9 Managing Database Connections . 9 Using Connection Pooling . 10 Storing Connection Strings . 15 Connection Usage Patterns . 20 Error Handling . 22 .NET Exceptions. 22 Generating Errors from Stored Procedures . 26 Performance . 29 Retrieving Multiple Rows . 29 Retrieving a Single Row .
    [Show full text]
  • Pervasive Data Provider for .NET Guide and Reference
    Pervasive PSQL 11 Pervasive Data Provider for .NET Guide and Reference Developing Applications with Data Provider for .NET Pervasive Software Inc. 12365 Riata Trace Parkway Building B Austin, TX 78727 USA Telephone: 512 231 6000 or 800 287 4383 Fax: 512 231 6010 Email: [email protected] Web: http://www.pervasivedb.com disclaimer PERVASIVE SOFTWARE INC. LICENSES THE SOFTWARE AND DOCUMENTATION PRODUCT TO YOU OR YOUR COMPANY SOLELY ON AN “AS IS” BASIS AND SOLELY IN ACCORDANCE WITH THE TERMS AND CONDITIONS OF THE ACCOMPANYING LICENSE AGREEMENT. PERVASIVE SOFTWARE INC. MAKES NO OTHER WARRANTIES WHATSOEVER, EITHER EXPRESS OR IMPLIED, REGARDING THE SOFTWARE OR THE CONTENT OF THE DOCUMENTATION; PERVASIVE SOFTWARE INC. HEREBY EXPRESSLY STATES AND YOU OR YOUR COMPANY ACKNOWLEDGES THAT PERVASIVE SOFTWARE INC. DOES NOT MAKE ANY WARRANTIES, INCLUDING, FOR EXAMPLE, WITH RESPECT TO MERCHANTABILITY, TITLE, OR FITNESS FOR ANY PARTICULAR PURPOSE OR ARISING FROM COURSE OF DEALING OR USAGE OF TRADE, AMONG OTHERS. trademarks Btrieve, Client/Server in a Box, Pervasive, Pervasive Software, and the Pervasive Software logo are registered trademarks of Pervasive Software Inc. Built on Pervasive Software, DataExchange, MicroKernel Database Engine, MicroKernel Database Architecture, Pervasive.SQL, Pervasive PSQL, Solution Network, Ultralight, and ZDBA are trademarks of Pervasive Software Inc. Microsoft, MS-DOS, Windows, Windows 95, Windows 98, Windows NT, Windows Millennium, Windows 2000, Windows XP, Win32, Win32s, and Visual Basic are registered trademarks of Microsoft Corporation. NetWare and Novell are registered trademarks of Novell, Inc. NetWare Loadable Module, NLM, Novell DOS, Transaction Tracking System, and TTS are trademarks of Novell, Inc. Sun, Sun Microsystems, Java, all trademarks and logos that contain Sun, Solaris, or Java, are trademarks or registered trademarks of Sun Microsystems.
    [Show full text]
  • Getting Started with DB XML Java
    Getting Started with DB XML For Java Steve Sarette Makers of Berkeley DB 2 GETTING STARTED WITH DB XML FOR JAVA GETTING STARTED WITH DB XMl FOR JAVA 3 Legal Notice This work is licensed under the Creative Commons Attribution-ShareAlike License. To view a copy of this license, visit http://www.sleepycat.com/download/cd/commonsdeed.html or send a letter to: Creative Commons 559 Nathan Abbott Way Stanford, California 94305 USA The text and example code included in this document are distributed under the Creative Commons license. Sleepycat Software, Berkeley DB, Berkeley DB XML and the Sleepycat logo are trademarks or service marks of Sleepycat Software, Inc. All rights to these marks are reserved. No third-party use is permitted without the express prior written consent of Sleepycat Software, Inc. 2 GETTING STARTED WITH DB XML FOR JAVA GETTING STARTED WITH DB XMl FOR JAVA 3 Getting Started with DB XML For Java Table of Contents 1. Introduction to Berkeley DB XML Features Languages and Platforms XML Features Database Features Getting and Using DBXML Documentation and Support Library Dependencies Building and Running DBXML Applications 2. Using Containers and Environments Opening and Closing Containers Using Containers with Berkeley DB Environments Database Open Flags 3. Adding Documents to DBXML 4. Using XPath with DBXML XPath: A Brief Introduction Selecting Text Nodes Selecting Attribute Nodes Context Predicates Wildcards Retrieving DBXML Documents using XPath Examples Document Set Performing Requests Setting a Context Retrieving Document Data using XPath 5. Deleting and Replacing Documents in DBXML Deleting Documents from DBXML Containers Replacing Documents in DBXML Containers 6.
    [Show full text]
  • Benchmarking Virtuoso 8 at the Mighty Storage Challenge 2018: Challenge Results
    Benchmarking Virtuoso 8 at the Mighty Storage Challenge 2018: Challenge Results Milos Jovanovik1;2 and Mirko Spasi´c1;3 1 OpenLink Software, United Kingdom 2 Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia 3 Faculty of Mathematics, University of Belgrade, Serbia {mjovanovik,mspasic}@openlinksw.com Abstract. Following the success of Virtuoso at last year's Mighty Stor- age Challenge - MOCHA 2017, we decided to participate once again and test the latest Virtuoso version against the new tasks which comprise the MOCHA 2018 challenge. The aim of the challenge is to test the performance of solutions for SPARQL processing in aspects relevant for modern applications: ingesting data, answering queries on large datasets and serving as backend for applications driven by Linked Data. The chal- lenge tests the systems against data derived from real applications and with realistic loads, with an emphasis on dealing with changing data in the form of streams or updates. Virtuoso, by OpenLink Software, is a modern enterprise-grade solution for data access, integration, and rela- tional database management, which provides a scalable RDF Quad Store. In this paper, we present the final challenge results from MOCHA 2018 for Virtuoso v8.0, compared to the other participating systems. Based on these results, Virtuoso v8.0 was declared as the overall winner of MOCHA 2018. Keywords: Virtuoso, Mighty Storage Challenge, MOCHA, Benchmarks, Data Storage, Linked Data, RDF, SPARQL 1 Introduction Last year's Mighty Storage Challenge, MOCHA 2017, was quite successful for our team and Virtuoso { we won the overall challenge [6, 11].
    [Show full text]
  • Three Decades of Data Integration — All Problems Solved?
    THREE DECADES OF DATA INTEGRATION — ALL PROBLEMS SOLVED? Patrick Ziegler and Klaus R. Dittrich Database Technology Research Group, Department of Informatics, University of Zurich Winterthurerstrasse 190, CH-8057 Zürich, Switzerland {pziegler|dittrich}@ifi.unizh.ch Abstract Data integration is one of the older research fields in the database area and has emerged shortly after database systems were first introduced into the business world. In this paper, we briefly introduce the problem of integration and, based on an architectural perspective, give an overview of approaches to address the integration issue. We discuss the evolution from structural to semantic integra- tion and provide a short outlook on our own research in the SIRUP (Semantic Integration Reflecting User-specific semantic Perspectives) approach. Keywords: Data integration, integration approaches, semantic integration 1. Introduction In today’s business world, it is typical that enterprises run different but co- existing information systems. Employing these systems, enterprises struggle to realize business opportunities in highly competitive markets. In this setting, the integration of existing information systems is becoming more and more in- dispensable in order to dynamically meet business and customer needs while leveraging long-term investments in existing IT infrastructure. In general, integration of multiple information systems aims at combining selected systems so that they form a unified new whole and give users the illu- sion of interacting with one single information system. The reason for integra- tion is twofold: First, given a set of existing information systems, an integrated view can be created to facilitate information access and reuse through a single information access point. Second, given a certain information need, data from different complementing information systems is to be combined to gain a more comprehensive basis to satisfy the need.
    [Show full text]
  • Data Access with ADO.NET by Andrew Troelsen
    APPENDIX Data Access with ADO.NET by Andrew Troelsen This is Chapter 13 of C#and the .NET Platform (Apress, 2001). From this point on, all references to other chapters and appendixes are to those from Troelsen and not to chapters and appendixes within Distributed .NET Programming in C#. Unless you are a video game developer by trade, you are probably interested in data­ base manipulation. As you would expect, the .NET platform defines a number of types (in a handful of related namespaces) that allow you to interact with local and remote data stores. Collectively speaking, these namespaces are known as ADO.NET, which as you will see is a major overhaul of the classic ADO object model. This chapter begins by examining some core types defined in the System.Data namespace-specifically DataColumn, DataRow, and DataTable. These classes allow you to define and manipulate a local in-memory table of data. Next, you spend a good deal of time learning about the centerpiece of ADO.NET, the DataSet. As you will see, the DataSet is an in-memory representa­ tion of a collection of interrelated tables. During this discussion, you will learn how to programmatically model table relationships, create custom views from a given table, and submit queries against your in-memory DataSet. After discussing how to manipulate a DataSet in memory, the remainder of this chapter illustrates how to obtain a populated DataSet from a Database Man­ agement System (DBMS) such as MS SQL Server, Oracle, or MS Access. This entails an examination of .NET "managed providers" and the OleDbDataAdapter and SqlDataAdapter types.
    [Show full text]