Distributed Graph DBMSs — The Future for Analytics on Big Data?
summary
The talk examines distributed graph databases for big-data analytics, contrasting them with traditional single-node systems like Neo4j and addressing concerns about performance and scalability across multiple nodes. It reviews recent developments and architectures that aim to make graph DBMSs suitable for large-scale analytical workloads.
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chapters (11)
- 0:00Introduction
- 1:37What are graph DBs
- 5:12Traditional graph analytics
- 14:52Graph analytics examples
- 17:44Graph algorithms for analytics
- 18:25Machine learning on graphs
- 27:07Graph DB challenges
- 30:38Hybrid systems future
- 31:01Getting started with graph DBs
- 34:32Summary and outlook
- 34:53Q&A
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