<section id="benchmarks">
  <div class="container">
    <h2>Benchmarks</h2>
    <p>ML ranking workload: 1000 documents × 10 float32 columns, random keys, 10M row dataset.</p>
    <table class="bench-table">
      <thead>
        <tr>
          <th>Approach</th>
          <th>Latency</th>
          <th>95% CI</th>
          <th>Throughput</th>
        </tr>
      </thead>
      <tbody>
        <tr class="highlight">
          <td>Murr (HTTP + Arrow IPC)</td>
          <td>104 µs</td>
          <td>[103—104 µs]</td>
          <td>9.63 Mkeys/s</td>
        </tr>
        <tr class="highlight">
          <td>Murr (Flight gRPC)</td>
          <td>105 µs</td>
          <td>[104—105 µs]</td>
          <td>9.53 Mkeys/s</td>
        </tr>
        <tr>
          <td>Redis MGET (feature blobs)</td>
          <td>263 µs</td>
          <td>[262—264 µs]</td>
          <td>3.80 Mkeys/s</td>
        </tr>
        <tr>
          <td>Redis Feast (HSET per row)</td>
          <td>3.80 ms</td>
          <td>[3.76—3.89 ms]</td>
          <td>263 Kkeys/s</td>
        </tr>
      </tbody>
    </table>
    <p class="bench-note">~2.5x faster than the best Redis layout, ~36x faster than Feast-style storage. Last-byte latency measured.</p>
    <a href="{{ .Site.Params.github }}#benchmarks" class="section-link">Methodology details</a>
  </div>
</section>
