<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Causal Cluster on PlumePHP</title><link>https://plumephp.com/tags/causal-cluster/</link><description>Recent content in Causal Cluster on PlumePHP</description><generator>Hugo</generator><language>zh-CN</language><lastBuildDate>Sat, 26 Sep 2026 14:00:00 +0800</lastBuildDate><atom:link href="https://plumephp.com/tags/causal-cluster/index.xml" rel="self" type="application/rss+xml"/><item><title>图数据库选型与集群运维：从 Causal Cluster 到分布式对比</title><link>https://plumephp.com/graphdb-cluster-operations/</link><pubDate>Sat, 26 Sep 2026 14:00:00 +0800</pubDate><guid>https://plumephp.com/graphdb-cluster-operations/</guid><description>&lt;h2 id="导语当图数据变成关键基础设施"&gt;导语：当图数据变成关键基础设施&lt;/h2&gt;
&lt;p&gt;单机 Neo4j 能支撑千万级节点，但当图数据成为关键业务基础设施（风控、供应链、社交），高可用与水平扩展就不是选项而是底线。本文聚焦生产级集群运维：从 Neo4j 的 Causal Cluster 因果一致性、读写分离，到分片与复制、备份恢复、监控告警，最后对比 NebulaGraph、JanusGraph、Dgraph 的集群架构差异（概念基础见 &lt;a href="https://plumephp.com/graphdb-comparison/"&gt;图数据库选型对比&lt;/a&gt;）。&lt;/p&gt;</description></item></channel></rss>