Designing the Right PostgreSQL Index Using Query Plans and Statistics

<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

<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>PROFESSIONAL DJANGO ENGINEERING SERIES #6</p> <blockquote> <p>If you have never read a query execution plan, you are flying blind on database performance. Here is how to read

<p>Ever spent hours wondering why your SQL queries are dragging your app down, or why your database server is at 90% CPU with just a handful of users? You're not alone. Slow SQL

<p>If your app has a slow endpoint and you're staring at application logs trying to guess which query is the culprit, stop. Postgres already tracked every query it ran, how long

<p>Hello, I'm Tuan.</p> <p>When backend engineers encounter a slow query, the first instinct is often something like:</p> <blockquote> <p>"Check the WHERE and ORDER BY, then just

<p>Let's consider a table <code>user</code>. When we execute a query to find <code>Emily</code>, we are actually going through <strong>each record</strong>, looking whether the

<p>When we write:<br /> </p> <div class="highlight js-code-highlight"> <pre class="highlight sql"><code><span class="k">SELECT</span> <span class="o">*</span> <span