mlsanityData to 14 Oct 2026

SchemaDB: Structures in Relational Datasets

arXiv 2111.12835 ↗First posted 24 Nov 2021cs.DB cs.LGcited by 2

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Abstract (arXiv)

In this paper we introduce the SchemaDB data-set; a collection of relational database schemata in both sql and graph formats. Databases are not commonly shared publicly for reasons of privacy and security, so schemata are not available for study. Consequently, an understanding of database structures in the wild is lacking, and most examples found publicly belong to common development frameworks or are derived from textbooks or engine benchmark designs. SchemaDB contains 2,500 samples of relational schemata found in public repositories which we have standardised to MySQL syntax. We provide our gathering and transformation methodology, summary statistics, and structural analysis, and discuss potential downstream research tasks in several domains.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 5 of its 13 references that are in the map. First posted on arXiv 24 Nov 2021.

Builds on

5 of 13 references.

References · 5

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2018GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Modelscited by 413
  3. 2019Efficient Graph Generation with Graph Recurrent Attention Networkscited by 234
  4. 2018Learning Deep Generative Models of Graphscited by 229
  5. 2020DeepGG: a Deep Graph Generatorcited by 4

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Citing papers per year: 2022: 1; 2023: 0; 2024: 0; 2025: 1.

2 papers.