<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Hash-Map on Pi Stack</title>
    <link>https://www.pistack.xyz/tags/hash-map/</link>
    <description>Recent content in Hash-Map on Pi Stack</description>
    <generator>Hugo</generator>
    <language>en-us</language>
    <lastBuildDate>Fri, 19 Jun 2026 00:00:00 +0000</lastBuildDate>
    <atom:link href="https://www.pistack.xyz/tags/hash-map/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>Self-Hosted Concurrent Hash Map Libraries: Dashmap vs Flurry vs Evmap vs Folly AtomicHashMap</title>
      <link>https://www.pistack.xyz/posts/2026-06-19-concurrent-hashmap-libraries-dashmap-flurry-evmap-folly/</link>
      <pubDate>Fri, 19 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://www.pistack.xyz/posts/2026-06-19-concurrent-hashmap-libraries-dashmap-flurry-evmap-folly/</guid>
      <description>&lt;p&gt;Modern multi-threaded applications demand data structures that scale across CPU cores without bottlenecks. A standard &lt;code&gt;HashMap&lt;/code&gt; wrapped in a mutex becomes a serialization point — only one thread can access the map at a time, killing performance under contention. Concurrent hash map libraries solve this by allowing multiple threads to read and write simultaneously using lock-free algorithms, fine-grained locking, or sharding.&lt;/p&gt;</description>
    </item>
  </channel>
</rss>
