Tentris - A Tensor-Based Triple Store (ISWC 2020 - 19th International Semantic Web Conference)
Channel: DICE - Data Science Group - Paderborn University
Date: 2022-10-18

Tentris - A Tensor-Based Triple Store
https://tentris.dice-research.org/
https://tentris.dice-research.org/iswc2020/
https://github.com/dice-group/tentris

Slides:
https://papers.dice-research.org/2020/ISWC_Tentris/iswc2020_tentris_presentation_public.pdf

Article:
Bigerl, Alexander, Conrads, Felix, Behning, Charlotte, Sherif, Mohamed, Saleem, Muhammad and Ngonga Ngomo, Axel-Cyrille. "Tentris – A Tensor-Based Triple Store." (2020): The Semantic Web – ISWC 2020.
https://doi.org/10.1007/978-3-030-62419-4_4
https://papers.dice-research.org/2020/ISWC_Tentris/iswc2020_tentris_public.pdf

Abstract:
The number and size of RDF knowledge graphs grows continuously. Efficient storage solutions for these graphs are indispensable for their use in real applications. We present such a storage solution dubbed Tentris. Our solution represents RDF knowledge graphs as sparse order-3 tensors using a novel data structure, which we dub hypertrie. It then uses tensor algebra to carry out SPARQL queries by mapping SPARQL operations to Einstein summation. By being able to compute Einstein summations efficiently, Tentris outperforms the commercial and open-source RDF storage solutions evaluated in our experiments by at least 1.8 times with respect to the average number of queries it can serve per second on three datasets of up to 1 billion triples.