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  <title>CSV import benchmarks — Scriptella</title>
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      <h1>CSV import benchmarks</h1>
      <p class="lede">One million rows, two databases, and a reproducible comparison of Scriptella 1.6, handwritten JDBC, and csvsql.</p>
      <p>Batched Scriptella imported the fixture in 14.79 seconds on PostgreSQL and 9.52 seconds on MariaDB on a local development machine. Handwritten JDBC was faster; csvsql’s tested direct-import workflow took about 9–10 minutes.</p>
      <p>These are exploratory results for this workload and environment. JDBC batching and csvsql chunking use different mechanisms; PostgreSQL COPY is a database-specific reference.</p>

      <h2 id="local-results">Local development machine</h2>
      <p>The charts show median durations from two runs of the same million-row import. Lower is faster.</p>
      <figure>
        <img src="images/benchmarks/local-postgres.svg" width="879" height="447" alt="Local PostgreSQL durations: Scriptella 14.792 seconds, JDBC 13.631 seconds, csvsql 557.945 seconds, and native COPY 1.672 seconds.">
        <figcaption>PostgreSQL: logarithmic duration axis. Read the printed seconds for absolute differences.</figcaption>
      </figure>
      <figure>
        <img src="images/benchmarks/local-mariadb.svg" width="879" height="447" loading="lazy" alt="Local MariaDB durations: Scriptella 9.523 seconds, JDBC 6.649 seconds, and csvsql 597.053 seconds.">
        <figcaption>MariaDB: logarithmic duration axis. Read the printed seconds for absolute differences.</figcaption>
      </figure>
      <p>Measured on an Intel Core i9 Mac using Docker through Colima. See the <a href="https://github.com/scriptella/scriptella-benchmarks/tree/main/docs/results/2026-10-12-local">full results and environment details</a>, including individual runs and unbatched imports.</p>

      <h2 id="method">About the comparison</h2>
      <p>All import paths load the same CSV into a pre-created table, with one transaction per import and no indexes or transformations. Timings include client startup, parsing, insertion, and commit; setup and verification are excluded. Every measured import passed independent row-count and sampled-value checks.</p>
      <p>The experiment uses Scriptella 1.6, Java 17, csvsql 2.2.0, PostgreSQL 17.11, and MariaDB 11.8.8 with normal database and driver defaults. See the <a href="https://github.com/scriptella/scriptella-benchmarks#measurement-method">methodology and limitations</a> for the full comparison.</p>

      <h2 id="ci-results">GitHub Actions reproduction</h2>
      <p>A separate Ubuntu 24.04 run showed the same ordering: batched Scriptella imported the million rows in 6.86 seconds on PostgreSQL and 4.45 seconds on MariaDB. These are single observations, kept separate from the local medians. See the <a href="https://github.com/scriptella/scriptella-benchmarks/tree/main/docs/results/2026-10-13-ci">CI results</a>.</p>

      <h2 id="reproduce">Run it yourself</h2>
      <p>The benchmark runs with Docker Compose and includes all dependencies. The <a href="https://github.com/scriptella/scriptella-benchmarks#run-the-comparison">repository instructions</a> cover running the comparison, inspecting results, and repeating it on your own hardware.</p>

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