The VLDB Journal

, Volume 10, Issue 4, pp 334–350 | Cite as

A survey of approaches to automatic schema matching

  • Erhard Rahm
  • Philip A. Bernstein
Regular contribution


Schema matching is a basic problem in many database application domains, such as data integration, E-business, data warehousing, and semantic query processing. In current implementations, schema matching is typically performed manually, which has significant limitations. On the other hand, previous research papers have proposed many techniques to achieve a partial automation of the match operation for specific application domains. We present a taxonomy that covers many of these existing approaches, and we describe the approaches in some detail. In particular, we distinguish between schema-level and instance-level, element-level and structure-level, and language-based and constraint-based matchers. Based on our classification we review some previous match implementations thereby indicating which part of the solution space they cover. We intend our taxonomy and review of past work to be useful when comparing different approaches to schema matching, when developing a new match algorithm, and when implementing a schema matching component.

Key words: Schema matching – Schema integration – Graph matching – Model management – Machine learning 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Erhard Rahm
    • 1
  • Philip A. Bernstein
    • 2
  1. 1.Universität Leipzig, Institut für Informatik, 04109 Leipzig, Germany; (e-mail:
  2. 2.Microsoft Research, Redmond, WA 98052-6399, USA; (e-mail:

Personalised recommendations