Introduction to Databases: From Biological to Spatio-Temporal
Introduced forty years ago, relational databases proved unusually succe- ful and durable. However, relational database systems were not designed for modern applications and computers. As a result, specialized database systems now proliferate trying to capture various pieces of the database market. Database research is pulled into different directions, and speci- ized database conferences are created. Yet the current chaos in databases is likely only temporary because every technology, including databases, becomes standardized over time. The history of databases shows periods of chaos followed by periods of dominant technologies. For example, in the early days of computing, users stored their data in text—les in any format and organization they wanted. These early days were followed by information retrieval systems, which required some structure for text documents, such as a title, authors, and a publisher. The information retrieval systems were followed by database systems, which addedeven more structure to the data and made querying easier. In the late 1990s, the emergence of the Internet brought a period of relative chaos and interest in unstructured and “semistructured data” as it was envisioned that every webpage would be like a page in a book. However, with the growing maturity of the Internet, the interest in structured data was regained because the most popular websites are, in fact, based on databases. The question is not whether future data stores need structure but what structure they need.
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Introduction to Databases: From Biological to Spatio-Temporal
Introduced forty years ago, relational databases proved unusually succe- ful and durable. However, relational database systems were not designed for modern applications and computers. As a result, specialized database systems now proliferate trying to capture various pieces of the database market. Database research is pulled into different directions, and speci- ized database conferences are created. Yet the current chaos in databases is likely only temporary because every technology, including databases, becomes standardized over time. The history of databases shows periods of chaos followed by periods of dominant technologies. For example, in the early days of computing, users stored their data in text—les in any format and organization they wanted. These early days were followed by information retrieval systems, which required some structure for text documents, such as a title, authors, and a publisher. The information retrieval systems were followed by database systems, which addedeven more structure to the data and made querying easier. In the late 1990s, the emergence of the Internet brought a period of relative chaos and interest in unstructured and “semistructured data” as it was envisioned that every webpage would be like a page in a book. However, with the growing maturity of the Internet, the interest in structured data was regained because the most popular websites are, in fact, based on databases. The question is not whether future data stores need structure but what structure they need.
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Introduction to Databases: From Biological to Spatio-Temporal

Introduction to Databases: From Biological to Spatio-Temporal

by Peter Revesz
Introduction to Databases: From Biological to Spatio-Temporal

Introduction to Databases: From Biological to Spatio-Temporal

by Peter Revesz

Overview

Introduced forty years ago, relational databases proved unusually succe- ful and durable. However, relational database systems were not designed for modern applications and computers. As a result, specialized database systems now proliferate trying to capture various pieces of the database market. Database research is pulled into different directions, and speci- ized database conferences are created. Yet the current chaos in databases is likely only temporary because every technology, including databases, becomes standardized over time. The history of databases shows periods of chaos followed by periods of dominant technologies. For example, in the early days of computing, users stored their data in text—les in any format and organization they wanted. These early days were followed by information retrieval systems, which required some structure for text documents, such as a title, authors, and a publisher. The information retrieval systems were followed by database systems, which addedeven more structure to the data and made querying easier. In the late 1990s, the emergence of the Internet brought a period of relative chaos and interest in unstructured and “semistructured data” as it was envisioned that every webpage would be like a page in a book. However, with the growing maturity of the Internet, the interest in structured data was regained because the most popular websites are, in fact, based on databases. The question is not whether future data stores need structure but what structure they need.

Product Details

ISBN-13: 9781447125334
Publisher: Springer London
Publication date: 03/07/2012
Series: Texts in Computer Science
Edition description: 2010
Pages: 743
Product dimensions: 8.27(w) x 10.98(h) x 0.06(d)

Table of Contents

Data Models, Queries, Evaluation.- Propositional Databases.- Relational Databases.- Constraint Databases.- Temporal Databases.- Geographic Databases.- Moving Objects Databases.- Image Databases.- Constraint Objects Databases.- Genome Databases.- Set Databases.- Constraint Deductive Databases.- The MLPQ System.- The DISCO System.- Database Design.- Interoperability.- Data Integration.- Interpolation and Approximation.- Prediction and Data Mining.- Indexing.- Data Visualization.- Safe Query Languages.- Evaluation of Queries.- Implementation Methods.- Computational Complexity.- Software Verification.

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