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InfoQ Homepage Presentations Causal Consistency for Large Neo4j Clusters

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Causal Consistency for Large Neo4j Clusters

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49:40

Summary

Jim Webber explores the new Causal clustering architecture for Neo4j, showing that, despite the mixture of consensus protocols and asynchronous replication, Neo4j allows users to read their own writes straightforwardly, and discusses why this is such a difficult achievement in distributed systems.

Bio

Jim Webber is Chief Scientist with Neo Technology, the company behind the popular open source graph database Neo4j. He works on R&D for highly scalable graph databases and writes open source software. He has written two books on integration and distributed systems: “Developing Enterprise Web Services” and “REST in Practice”. His latest book is “Graph Databases” which focuses on the Neo4j database.

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Recorded at:

Apr 07, 2017

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