MaDI-Bench: An End-to-End Data Integration Benchmark

Abstract:Data integration is the process of combining data from multiple, heterogeneous sources into a consistent, unified representation. Data integration involves a sequence of interdependent tasks including schema matching, value normalization, blocking, entity matching, and data fusion. Existing table-based benchmarks either evaluate these steps in isolation or cover only incomplete versions of the data integration pipeline, omitting specific steps. The lack of public end-to-end data integration benchmarks hinders research on data integration methods that address the integration process as a whole and account for the interdependencies among the different tasks. This paper fills this gap by introducing the Mannheim Data Integration Benchmark (MaDI-Bench), the first benchmark for the end-to-end integration of relational tables covering all steps of the integration process. MaDI-Bench contributes (i) a set of end-to-end data integration tasks spanning several application domains, each requiring the full schema matching, value normalization, entity matching, and data fusion pipeline, and (ii) a generic method for deriving task variants that mitigates rapid benchmark saturation as data integration systems advance. We validate the benchmark using human-engineered pipelines, a best-of-breed pipeline, an LLM workflow, and a pipeline written by a coding agent. The validation demonstrates the utility of the benchmark for measuring the step-wise as well as the end-to-end performance of data integration pipelines. All benchmark artifacts are available for public download.

13 pages, 1 figure, 14 tables. Revised version: four pipelines, normalization evaluation, task variants

Databases (cs.DB); Computation and Language (cs.CL)

H.2.5; H.2.4; H.2.8

arXiv:2606.30371 [cs.DB]

(or arXiv:2606.30371v2 [cs.DB] for this version)

https://doi.org/10.48550/arXiv.2606.30371 Focus to learn more arXiv-issued DOI via DataCite

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