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Samih Sayloğlu | Serverless In-Process Graph Analytics & RAG Workflows | Graph the planet 2025
Join Samih Sayloğlu, co-founder of Kuzu Inc. and Professor of Database Systems at the University of Waterloo, at Graph the Planet 2025 to discover KuzuDB—a lightning-fast, in-process graph database designed for modern RAG and graph-powered apps.
In this talk you’ll see:
In-Process Architecture: How KuzuDB embeds directly into your app, Lambda function, or browser—no standalone server required
On-Demand Graphs from Parquet: Creating transient, query-optimized graphs over S3 data in real time via AWS Lambda
Native Vector & Full-Text Indexes: Disk-based HNSW for nearest-neighbor retrieval plus BM25 text search built right in
Python-First Experience: Seamless Cypher queries, pandas-style dataframes, Arrow export, and NetworkX interoperability
Performance at Scale: Loading the LDBC benchmark’s 447M nodes & 1.7B edges in under an hour—plus real-world bulk-load metrics
Hybrid RAG & Graph Workflows: Combining vector search with graph traversals for precise retrieval-augmented generation
Roadmap Preview: Upcoming features like geospatial support, in-browser bindings, and enterprise cloud editions
🔗 Resources & Links
• Explore KuzuDB → https://kuzudb.com
• Graph the Planet Conference → https://graphtheplanet.ai
👍 If you’re building next-gen graph apps or RAG pipelines, like, subscribe, and hit the 🔔 for more deep dives into cutting-edge graph technologies!
#GraphThePlanet #KuzuDB #GraphDatabase #RAG #VectorSearch #FullTextSearch #InProcessDB #ServerlessGraph
Видео Samih Sayloğlu | Serverless In-Process Graph Analytics & RAG Workflows | Graph the planet 2025 канала Graphistry
In this talk you’ll see:
In-Process Architecture: How KuzuDB embeds directly into your app, Lambda function, or browser—no standalone server required
On-Demand Graphs from Parquet: Creating transient, query-optimized graphs over S3 data in real time via AWS Lambda
Native Vector & Full-Text Indexes: Disk-based HNSW for nearest-neighbor retrieval plus BM25 text search built right in
Python-First Experience: Seamless Cypher queries, pandas-style dataframes, Arrow export, and NetworkX interoperability
Performance at Scale: Loading the LDBC benchmark’s 447M nodes & 1.7B edges in under an hour—plus real-world bulk-load metrics
Hybrid RAG & Graph Workflows: Combining vector search with graph traversals for precise retrieval-augmented generation
Roadmap Preview: Upcoming features like geospatial support, in-browser bindings, and enterprise cloud editions
🔗 Resources & Links
• Explore KuzuDB → https://kuzudb.com
• Graph the Planet Conference → https://graphtheplanet.ai
👍 If you’re building next-gen graph apps or RAG pipelines, like, subscribe, and hit the 🔔 for more deep dives into cutting-edge graph technologies!
#GraphThePlanet #KuzuDB #GraphDatabase #RAG #VectorSearch #FullTextSearch #InProcessDB #ServerlessGraph
Видео Samih Sayloğlu | Serverless In-Process Graph Analytics & RAG Workflows | Graph the planet 2025 канала Graphistry
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16 мая 2025 г. 0:30:15
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