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      <title>Inside Netflix’s Graph Abstraction: Handling 650TB of Graph Data in Milliseconds Globally</title>
      <link>https://www.infoq.com/news/2026/03/netflix-graph-abstraction/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Graph+Database-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/03/netflix-graph-abstraction/en/headerimage/netflixgrapharchitecure-1773194590219.jpeg"/&gt;&lt;p&gt;Netflix engineers built Graph Abstraction, a high-throughput platform managing 650 TB of graph data with millisecond latency. Supporting services from Netflix Gaming’s social graphs to operational topology graphs, it maintains global availability via asynchronous replication. This article covers its architecture, caching, and traversal design for high-scale performance.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Caching</category>
      <category>Low Latency</category>
      <category>Clustering &amp; Caching</category>
      <category>Distributed Systems</category>
      <category>Abstraction</category>
      <category>KVM</category>
      <category>gRPC</category>
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      <pubDate>Mon, 23 Mar 2026 13:54:00 GMT</pubDate>
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      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-03-23T13:54:00Z</dc:date>
      <dc:identifier>/news/2026/03/netflix-graph-abstraction/en</dc:identifier>
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