http://ddinsights.net/categories/concepts/Recent content in Concepts on Distributed Data InsightsHugoen-usSun, 07 Jun 2026 10:00:00 -0700http://ddinsights.net/posts/why-distributed-data-is-hard/Sun, 07 Jun 2026 10:00:00 -0700http://ddinsights.net/posts/why-distributed-data-is-hard/<p>Every distributed data system is an answer to the same uncomfortable question: <em>what do you do when part of your system fails but the rest keeps running?</em> On a single machine, a crash takes everything down together — clean, if catastrophic. Across a network, failure is <strong>partial</strong>, <strong>ambiguous</strong>, and <strong>constant</strong>.</p> <h2 id="the-three-things-the-network-takes-away">The three things the network takes away</h2> <p>When you split state across machines, you lose three guarantees you took for granted on a single box:</p>http://ddinsights.net/posts/quorums-and-tunable-consistency/Fri, 05 Jun 2026 09:00:00 -0700http://ddinsights.net/posts/quorums-and-tunable-consistency/<p>Many distributed databases — Dynamo-style stores like Cassandra and Riak — don&rsquo;t make you choose consistency once and for all. They let you tune it <strong>per request</strong> using quorums. The mechanism is simple arithmetic with surprisingly deep consequences.</p> <h2 id="the-setup">The setup</h2> <p>Each piece of data is replicated to <strong>N</strong> nodes. For every operation you pick:</p> <ul> <li><strong>W</strong> — how many replicas must acknowledge a <em>write</em> before it&rsquo;s considered done.</li> <li><strong>R</strong> — how many replicas you read from and compare before returning.</li> </ul> <p>The headline rule:</p>