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Keynote | Technical

Causal Consistency For Large Neo4j Clusters

Friday 17th | 10:40 - 11:10 | Theatre 19


One-liner summary:

An overview of the Raft algorithm and how Neo4j uses it to provide strong consistency at scale.

Keywords defining the session:

- Raft

- Neo4j

- Consistency

Takeaway points of the session:

- Raft algorithm Very large Neo4j clusters

- Distributed systems

Description:

An overview of the Raft algorithm and how Neo4j uses it to provide strong consistency at scale.In this talk, we’ll explore the new Causal clustering architecture for Neo4j. We’ll see how Neo4j uses the Raft protocol for a robust underlay for intensive write operations, and how the asynchronous new scale-out mechanism provides enormous capacity for very demanding graph workloads.

 

We’ll discuss the cluster architecture’s new causal consistency model. Causal consistency is a big leap forward compared to the commonplace eventual consistency which makes it convenient to write applications that use the full capacity of the cluster. In particular, we’ll show how despite the mixture of consensus protocols and asynchronous replication, that Neo4j allows users to read their own writes straightforwardly and discuss why this is such a difficult achievement in distributed systems.

For the application developer, we’ll show how Neo4j’s Causal Clustering optimised drivers makes it easy to write applications that scale smoothly from a single server to a large, distributed cluster: a practical motivation for the distributed systems enthusiast.