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      <title>The Problem: Database Bottlenecks</title>
      <dc:creator>larkana news tv</dc:creator>
      <pubDate>Wed, 14 Oct 2026 15:45:37 +0000</pubDate>
      <link>https://dev.to/larkana_newstv_307a1bb67/the-problem-database-bottlenecks-5em</link>
      <guid>https://dev.to/larkana_newstv_307a1bb67/the-problem-database-bottlenecks-5em</guid>
      <description>&lt;p&gt;Imagine an endpoint that fetches a high-volume resource—like product catalogs or user profiles—from MongoDB or PostgreSQL:.... &lt;a href="https://uplcm.com/4/8066840" rel="noopener noreferrer"&gt;Read more&lt;/a&gt; &lt;/p&gt;

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      <title>How I Optimized API Response Times by 70% with Redis &amp; Node.js</title>
      <dc:creator>larkana news tv</dc:creator>
      <pubDate>Wed, 14 Oct 2026 15:41:46 +0000</pubDate>
      <link>https://dev.to/larkana_newstv_307a1bb67/how-i-optimized-api-response-times-by-70-with-redis-nodejs-4op6</link>
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      <description>&lt;p&gt;all been there: your app is growing, traffic is picking up, and suddenly your database queries start dragging down response times. A simple endpoint fetching user dashboards or product listings goes from taking 40ms to 800ms+.&lt;br&gt;
​In this article, I’ll walk you through a practical, real-world guide on how to implement Redis caching in a Node.js/Express API to drastically reduce database load and slash response &lt;a href="https://uplcm.com/4/8066796" rel="noopener noreferrer"&gt;times...Readmore&lt;/a&gt;&lt;/p&gt;

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      <category>javascript</category>
      <category>devweb</category>
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