A Crash Course on Graph DBMSs & Kùzu
Graphs, i.e., networks of nodes and edges, are one of the most natural logical data models (the other being tables/relations) to model application data. Graphs have been the data model of many database management systems (DBMSs) in history. This talk will serve as an introduction to modern graph DBMSs, which adopt the "property graph data model", which was originally introduced in the Neo4j system and is now more widely adopted across many other systems. I will begin by covering the history of DBMSs to place graph DBMSs in the context of the broader set of DBMS products. We will answer the following questions:
- When should one use a graph DBMSs over a relational DBMS, such as Postgres?
- When should one not use a graph DBMS over a relational DBMS?
- What are key competencies of graph DBMSs?
- What are common applications that use graph DBMSs?
- What are example queries that are more natural to ask in a graph-based query language over SQL?
- What are popular graph DBMSs and graph data science libraries in the market?
In the remainder of the talk, I will discuss a new graph DBMS called Kùzu (https://github.com/kuzudb/kuzu) that we are actively developing in my group. Kùzu is an embeddable DBMS, i.e., one that is imported as a library into applications with no server-client set up, and integrates with several popular graph data science libraries, especially in the Python ecosystem. Kùzu is open-sourced and available under a permissible license. I will describe the goals and vision of the system and discuss several usability features in depth.
David R. Cheriton Faculty Fellow
University of Waterloo in Canada
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2 Ekim Pazartesi 19:00
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