{
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  "@type": "article",
  "@id": "https://anchorfact.org/kb/learned-database-systems",
  "headline": "Learned Database Systems: AI-Driven Query Optimization, Learned Indexes, and Cardinality Estimation",
  "description": "Learned database systems replace decades of hand-tuned heuristics in databases with machine learning models. From learned indexes that replace B-trees with tiny neural networks to learned query optimizers that beat expert-designed cost models, AI is challenging the assumption that classical data structures and algorithms are always optimal for specific data distributions.",
  "dateCreated": "2026-05-24T02:49:13.627Z",
  "dateModified": "2026-05-24",
  "author": {
    "@type": "Organization",
    "name": "AnchorFact"
  },
  "publisher": {
    "@type": "Organization",
    "name": "AnchorFact",
    "url": "https://anchorfact.org"
  },
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "anchorfact:confidence": "high",
  "anchorfact:generationMethod": "ai_assisted",
  "citation": [
    {
      "@type": "CreativeWork",
      "name": "Learning database optimization techniques: the state-of-the-art and future directions",
      "sameAs": "https://link.springer.com/article/10.1007/s11704-025-41116-7"
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    {
      "@type": "CreativeWork",
      "name": "The Case for Learned Index Structures",
      "sameAs": "https://arxiv.org/abs/1712.01208"
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}