graph-data-management

Graph Processing Using Relational Operators

GraphflowDB and Modern Query Processing Techniques for GDBMSs, 1-hour lecture by Semih Salihoglu at Pinterest Labs (2021) [WCOJ] [FACT]
From joins to aggregates and optimization problems (slides), lecture by Dan Olteanu (2018) [WCOJ] [FACT]
From joins to aggregates and optimization problems, lectures series by Dan Olteanu (2018) [WCOJ] [FACT]
Factorised databases, slides, short lecture by Dan Olteanu (2017) [FACT]
SIGMOD 2020 tutorial: Optimal Join Algorithms Meet Top-k [WCOJ]
LIquid: Soul of a New Graph Database by Scott Meyer, presented at the University of Waterloo’s DSG Seminar Series
- YouTube
Relational databases can handle graphs too! Experiences with optimizing the Umbra RDBMS for LDBC SNB BI (slides) by Altan Birler (Technische Universität München), presented at the 15th LDBC TUC

⚡️ Graph Processing in RDBMSs by Kangfei Zhao, Jeffrey Xu Yu (IEEE Data Eng. Bull., 2017)

Papers from the University of Waterloo:

Other papers:

Adopting Worst-Case Optimal Joins in Relational Database Systems Michael Freitag et al. (VLDB 2020): WCOJs in the context of the Umbra compiled columnar RDBMS
Towards Multi-way Join Aware Optimizer in SAP HANA by Sungheun Wi et al. (VLDB 2020)
A Worst-Case Optimal Join Algorithm for SPARQL by Aidan Hogan et al. (ISWC 2019)

The case against specialized graph analytics engines (CIDR 2015), a paper showing how implementing graph algorithms (SSSP, PageRank, connected components) in T-SQL (Microsoft SQL Server) can outperform the implementations of dedicated graph analytics engines
In-database connected component analysis (ICDE 2020), a connected components implementation in SQL