The Hard Truth About Choosing a Database and Why Most Projects Get It Wrong

<p>PostgreSQL and MongoDB are both capable. The choice usually comes down to data shape, query patterns, team experience, and how much you care about schema and relations. Here’s

<p>Most applications don't fail because of bad code.</p> <p>They fail because of bad architecture decisions made early that nobody questioned <br /> until it was too late.</p>

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<p>Database selection is a critical decision, especially for indie hackers developing their own projects. Often, technology choices are driven by PR, and the daily impact of

<p>A good way to market a new infrastructure tool is to loudly announce that it is a thousand times faster than whatever you are currently using. This is a very effective strategy

<p>BACKEND ARCHITECTURE MASTERY</p> <h1> Day 8: Databases Part 1 - Postgres, orjson, and The Physics of Writes </h1> <p>15 min read</p> <p>Series: <strong>Logic &amp;

<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>I remember the exact moment our monolith’s database buckled under pressure. We’d just rolled out a new feature, usage spiked, and suddenly every other request was fighting for