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Data PDX: Kùzu Graph Database Management System

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Bio: Semih Salihoğlu is an Associate Professor and a David R. Cheriton Faculty Fellow at University of Waterloo. His research focuses on developing systems for managing, querying, or doing analytics on graph-structured data. His main on-going systems project is Kùzu, which is a new graph database management system that integrates novel storage, indexing and query processing techniques. He holds a PhD from Stanford University and is a recipient of the VLDB 2018 Best Paper and the VLDB 2022 Best Experiments and Analysis Paper awards.

Abstract: In this talk, I will present the Kùzu graph database management system (GDBMS) that we are developing at University of Waterloo. Datasets and workloads of popular applications that use GDBMSs require a set of storage and query processing features that relational DBMSs (RDBMSs) do not traditionally optimize for. These include optimizations for: (i) many-to-many (m-n) joins; (ii) cyclic joins; (iii) recursive joins; (iv) semi-structured data storage; and (v) support for universal resource identifiers. Kùzu aims to integrate state-of-art storage, indexing, and query processing techniques to highly optimize for this feature set. I will start by presenting the overall vision of Kùzu and then talk about the novel join operators in the system that performs joins using compressed factorized representations of intermediate tables. Kùzu is actively being developed to be a fully functional open-source DBMS with the goal of wide user adoption and under a permissible license.