Recent Increments in Incremental View Maintenance

TL;DR

This paper reviews recent theoretical and practical advances in incremental view maintenance (IVM), emphasizing complexity, optimality, and real-world applications, contributing to a deeper understanding of the IVM problem.

Contribution

It synthesizes recent progress in IVM, highlighting theoretical insights and practical engine developments that advance the understanding and application of incremental view maintenance.

Findings

Advances in fine-grained complexity analysis of IVM

Development of practical IVM engines with industrial benefits

Deeper understanding of IVM problem through combined progress

Abstract

We overview recent progress on the longstanding problem of incremental view maintenance (IVM), with a focus on the fine-grained complexity and optimality of IVM for classes of conjunctive queries. This theoretical progress guided the development of IVM engines that reported practical benefits in academic papers and industrial settings. When taken in isolation, each of the reported advancements is but a small increment. Yet when taken together, they may well pave the way to a deeper understanding of the IVM problem. This paper accompanies the invited Gems of PODS 2024 talk with the same title. Some of the works highlighted in this paper are based on prior or on-going collaborations with: Ahmet Kara, Milos Nikolic, and Haozhe Zhang in the F-IVM project; and Mahmoud Abo Khamis, Niko G\"obel, Hung Ngo, and Dan Suciu at RelationalAI.