Prisma Query Logging and PostgreSQL: Where the ORM Ends and the Database Begins

<p>A team notices a checkout endpoint slowing down. Response times have crept from 80ms to 900ms over two weeks, but the infrastructure dashboard shows nothing abnormal. So the

<p><em>B-tree internals, column order and planner statistics in Postgres 19, checked against MongoDB's ESR rule.</em></p> <p>Most "add an index" advice stops at <code>CREATE

<p>Hay una discusión que aparece cada vez que alguien postea un benchmark de ORM: "claro que JDBC es más rápido, estás midiendo la abstracción". Y tienen razón, pero solo a

<p>There's a discussion that surfaces every time someone posts an ORM benchmark: "of course JDBC is faster, you're measuring the abstraction". They're right, but only halfway.

<h2> I Thought My Index Would Fix Everything </h2> <p>I added the index.</p> <p>Ran the query.</p> <p>And… nothing changed.</p> <p>Same slow response. Same frustration.</p>

<p><strong>TL;DR:</strong> Postgres has <code>pg_stat_user_indexes</code>. It tells you how many times each index was scanned. It does <em>not</em> tell you whether the slow query

<p>PostgreSQL index design is often misunderstood.</p> <p>Many developers think that creating a good index simply means:</p> <blockquote> <p>“Create an index containing the

<p>Most slow PostgreSQL queries in Node.js REST APIs don’t happen because of missing database indexes.</p> <p>They happen because of silent N+1 query patterns executing inside map