Semih Salihoglu on creating Kùzu, the state of knowledge graphs, and the graph data landscape.
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Semih Salihoglu is an Associate Professor at University of Waterloo, and co-creator of Kuzu an open source embeddable property graph database management system. We discuss the appropriateness of Kuzu’s moniker (“DuckDB for graphs”), their recently launched startup, trends in graph databases and graph data science, and the potential role of graphs in Generative AI.
Interview highlights – key sections from the video version:
- Property Graphs: what and why
- Graph workloads: OLAP, OLTP, and beyond
- What motivated the development of Kuzu, and how does it differ from other graph database management systems?
- Embeddable database market: SQLite and DuckDB
- Kuzu is fast and it supports Cipher
- State of integration with popular programming languages, and Kuzu’s open source license
- Helping teams get started with graphs
- Kuzu is fast (part II)
- Multiple concurrent users
- Early Kuzu use cases
- State of graph machine learning and graph neural networks in industry
- Knowledge graphs and retrieval augmented generation
- Kuzu and graph visualization tools
- Kuzu’s community and contributors
Related content:
- A video version of this conversation is available on our YouTube channel.
- What Every Competent GDBMS Should Do (aka The Goals & Vision of Kùzu)
- What is Graph Intelligence?
- Emil Eifrem: The Future of Graph Databases
- Sudhir Hasbe: Trends in Data Management: From Source to BI and Generative AI
- Philipp Moritz and Goku Mohandas: Navigating the Nuances of Retrieval Augmented Generation
- Building a Fleet of Custom LLMs
- Ivy: Streamlining AI Model Deployment and Development
- Brian Raymond: ETL for LLMs
- Jerry Liu: An Open Source Data Framework for LLMs
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