Understanding RDF Data Representations in Triplestores

Matteo Lissandrini, Tomer Sagi, Torben Bach Pedersen, Katja Hose

Research output: Contribution to journalConference articlepeer-review


Because of the flexibility and expressiveness of their model, Knowledge Graphs (KGs) have received increasing interest. These resources are usually represented in RDF and stored in specialized data management systems called triplestores. Yet, while there exists a multitude of such systems, exploiting varying data representation and indexing schemes, it is unclear which of the many design choices are the most effective for a given database and query workload. Thus, first, we introduce a set of 20 access patterns, which we identify within 6 categories, adopted to analyze the needs of a given query workload. Then, we identify a novel three-dimensional design space for RDF data representations built on the dimensions of subdivision, redundancy, and compression of data. This design space maps the trade-offs between different RDF data representations employed to store RDF data within a triplestore. Thus, each of the required access patterns is compared against its compatibility with a given data representation. As we show, this approach allows identifying both the most effective RDF data representation for a given query workload as well as unexplored design solutions.

Original languageEnglish
Pages (from-to)93-100
Number of pages8
JournalCEUR Workshop Proceedings
StatePublished - 2022
Externally publishedYes
Event30th Italian Symposium on Advanced Database Systems, SEBD 2022 - Tirrenia, Italy
Duration: 19 Jun 202220 Jun 2022

Bibliographical note

Publisher Copyright:
© 2022 CEUR-WS. All rights reserved.


  • Data Management Systems Design
  • Knowledge Graphs
  • RDF Data Management

ASJC Scopus subject areas

  • General Computer Science


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