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    <title>scalability</title>
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    <updated>2026-04-20T09:03:18+00:00</updated>
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            <entry>
            <id>https://links.biapy.com/links/1961</id>
            <title type="text"><![CDATA[Garnet]]></title>
            <link rel="alternate" href="https://microsoft.github.io/garnet/" />
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            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A high-performance cache-store from Microsoft Research.

 Garnet is a remote cache-store from Microsoft Research that offers strong performance (throughput and latency), scalability, storage, recovery, cluster sharding, key migration, and replication features. Garnet can work with existing Redis clients. 

- [Garnet @ GitHub](https://github.com/microsoft/garnet).]]>
            </summary>
            <updated>2025-08-28T21:24:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4613</id>
            <title type="text"><![CDATA[awesome-scalability]]></title>
            <link rel="alternate" href="https://github.com/binhnguyennus/awesome-scalability" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4613"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Patterns of Scalable, Reliable, and Performant Large-Scale Systems.

An updated and organized reading list for illustrating the patterns of scalable, reliable, and performant large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken from battle-tested systems that serve millions to billions of users.]]>
            </summary>
            <updated>2025-08-29T04:46:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6792</id>
            <title type="text"><![CDATA[Haraka]]></title>
            <link rel="alternate" href="https://github.com/haraka/Haraka" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6792"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A fast, highly extensible, and event driven SMTP server.
Haraka is a highly scalable node.js email server with a modular plugin architecture. Haraka can serve thousands of concurrent connections and deliver thousands of messages per second. Haraka and plugins are written in asynchronous JS and are very fast.]]>
            </summary>
            <updated>2025-08-29T10:49:56+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/8352</id>
            <title type="text"><![CDATA[HBase - Apache HBase&amp;amp;#153; Home]]></title>
            <link rel="alternate" href="http://hbase.apache.org/" />
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            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Apache HBase™ is the Hadoop database, a distributed, scalable, big data store. 
Use Apache HBase when you need random, realtime read/write access to your Big Data. This project&amp;#039;s goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google&amp;#039;s Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, Apache HBase provides Bigtable-like capabilities on top of Hadoop and HDFS.]]>
            </summary>
            <updated>2025-08-29T15:09:22+00:00</updated>
        </entry>
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