2009•Proceedings of the VLDB EndowmentRequires access

Column-oriented database systems

Daniel J. Abadi, Peter A. Boncz, Stavros Harizopoulos

Open publisher page 239 citations

Abstract

Column-oriented database systems (column-stores) have attracted a lot of attention in the past few years. Column-stores, in a nutshell, store each database table column separately, with attribute values belonging to the same column stored contiguously, compressed, and densely packed, as opposed to traditional database systems that store entire records (rows) one after the other. Reading a subset of a table's columns becomes faster, at the potential expense of excessive disk-head seeking from column to column for scattered reads or updates. After several dozens of research papers and at least a dozen of new column-store start-ups, several questions remain. Are these a new breed of systems or simply old wine in new bottles? How easily can a major row-based system achieve column-store performance? Are column-stores the answer to effortlessly support large-scale data-intensive applications? What are the new, exciting system research problems to tackle? What are the new applications that can be potentially enabled by column-stores? In this tutorial, we present an overview of column-oriented database system technology and address these and other related questions.

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What this paper is about

Column-oriented database systems (column-stores) have attracted a lot of attention in the past few years. Column-stores, in a nutshell, store each database table column separately, with attribute values belonging to the same column stored contiguously, compressed, and densely packed, as opposed to traditional database systems that store entire records (rows) one after the other. Reading a subset of a table's columns becomes faster, at the potential expense of excessive disk-head seeking from column to column for scattered reads or updates. After several dozens of research papers and at least a dozen of new column-store start-ups, several questions remain. Are these a new breed of systems or simply old wine in new bottles? How easily can a major row-based system achieve column-store performance? Are column-stores the answer to effortlessly support large-scale data-intensive applications? What are the new, exciting system research problems to tackle? What are the new applications that can be potentially enabled by column-stores? In this tutorial, we present an overview of column-oriented database system technology and address these and other related questions.

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Available abstract

Column-oriented database systems (column-stores) have attracted a lot of attention in the past few years. Column-stores, in a nutshell, store each database table column separately, with attribute values belonging to the same column stored contiguously, compressed, and densely packed, as opposed to traditional database systems that store entire records (rows) one after the other. Reading a subset of a table's columns becomes faster, at the potential expense of excessive disk-head seeking from column to column for scattered reads or updates. After several dozens of research papers and at least a dozen of new column-store start-ups, several questions remain. Are these a new breed of systems or simply old wine in new bottles? How easily can a major row-based system achieve column-store performance? Are column-stores the answer to effortlessly support large-scale data-intensive applications? What are the new, exciting system research problems to tackle? What are the new applications that can be potentially enabled by column-stores? In this tutorial, we present an overview of column-oriented database system technology and address these and other related questions.

Key concepts: Column (typography), Row, Table (database), Computer science, Database, Row and column spaces, Telecommunications, Frame (networking)

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