<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Database Performance on Support Tools</title><link>https://support.tools/categories/database-performance/</link><description>Recent content in Database Performance on Support Tools</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Thu, 25 Sep 2025 09:00:00 -0500</lastBuildDate><atom:link href="https://support.tools/categories/database-performance/index.xml" rel="self" type="application/rss+xml"/><item><title>Benchmarking MongoDB vs PostgreSQL with Go: A Practical Performance Comparison</title><link>https://support.tools/post/benchmarking-mongodb-postgresql-with-go/</link><pubDate>Thu, 25 Sep 2025 09:00:00 -0500</pubDate><guid>https://support.tools/post/benchmarking-mongodb-postgresql-with-go/</guid><description>&lt;p&gt;When selecting a database for a production application, theoretical comparisons only get you so far. What matters is how the database performs with your specific workloads and access patterns. In this article, we&amp;rsquo;ll explore how to build a comprehensive benchmarking suite in Go to compare MongoDB and PostgreSQL across common real-world operations, providing actionable insights for your next project.&lt;/p&gt;&#10;&lt;h2 id="table-of-contents"&gt;Table of Contents&lt;/h2&gt;&#10;&lt;ol&gt;&#10;&lt;li&gt;&lt;a href="#introduction"&gt;Introduction&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#setting-up-the-environment"&gt;Setting Up the Environment&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#creating-realistic-test-datasets"&gt;Creating Realistic Test Datasets&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#benchmarking-methodology"&gt;Benchmarking Methodology&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#single-record-operations"&gt;Single-Record Operations&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#range-queries-and-filtering"&gt;Range Queries and Filtering&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#aggregation-performance"&gt;Aggregation Performance&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#pagination-and-sorting"&gt;Pagination and Sorting&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#write-operations"&gt;Write Operations&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#concurrency-testing"&gt;Concurrency Testing&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#results-analysis"&gt;Results Analysis&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#database-memory-and-cpu-usage"&gt;Database Memory and CPU Usage&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#real-world-scenarios-and-recommendations"&gt;Real-World Scenarios and Recommendations&lt;/a&gt;&lt;/li&gt;&#10;&lt;li&gt;&lt;a href="#conclusion"&gt;Conclusion&lt;/a&gt;&lt;/li&gt;&#10;&lt;/ol&gt;&#10;&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;&#10;&lt;p&gt;MongoDB and PostgreSQL represent two fundamentally different approaches to data storage and retrieval:&lt;/p&gt;</description></item></channel></rss>