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    <title>postgresql-licensed</title>
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    <updated>2026-04-26T08:37:12+00:00</updated>
    <id>https://links.biapy.com/guest/tags/3236/feed</id>
            <entry>
            <id>https://links.biapy.com/links/12389</id>
            <title type="text"><![CDATA[pg_textsearch]]></title>
            <link rel="alternate" href="https://github.com/timescale/pg_textsearch" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12389"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[PostgreSQL extension for BM25 relevance-ranked full-text search. Postgres OSS licensed.]]>
            </summary>
            <updated>2026-04-03T12:50:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12052</id>
            <title type="text"><![CDATA[🗄️ pg_semantic_cache]]></title>
            <link rel="alternate" href="https://github.com/pgEdge/pg_semantic_cache" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12052"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Intelligent Query Result Caching for PostgreSQL

Leverage vector embeddings to cache and retrieve query results based on semantic similarity.

- [Semantic Caching in PostgreSQL: A Hands-On Guide to pg_semantic_cache @ pgEdge](https://www.pgedge.com/blog/semantic-caching-in-postgresql-a-hands-on-guide-to-pg_semantic_cache).]]>
            </summary>
            <updated>2026-03-09T07:48:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11184</id>
            <title type="text"><![CDATA[pg_ivm]]></title>
            <link rel="alternate" href="https://github.com/sraoss/pg_ivm" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11184"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[IVM (Incremental View Maintenance) implementation as a PostgreSQL extension

Incremental View Maintenance (IVM) is a way to make materialized views up-to-date in which only incremental changes are computed and applied on views rather than recomputing the contents from scratch as REFRESH MATERIALIZED VIEW does. IVM can update materialized views more efficiently than recomputation when only small parts of the view are changed.

Related contents:

- [You Gotta Push If You Wanna Pull @ Gunnar Morling](https://www.morling.dev/blog/you-gotta-push-if-you-wanna-pull/).]]>
            </summary>
            <updated>2025-12-08T13:41:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10607</id>
            <title type="text"><![CDATA[Spock Multi-Master Replication for PostgreSQL]]></title>
            <link rel="alternate" href="https://github.com/pgEdge/spock?utm_source=tldrnewsletter" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10607"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Logical multi-master PostgreSQL replication.]]>
            </summary>
            <updated>2025-10-10T11:56:43+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10211</id>
            <title type="text"><![CDATA[pgFormatter]]></title>
            <link rel="alternate" href="https://sqlformat.darold.net/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10211"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A PostgreSQL SQL syntax beautifier that can work as a console program or as a CGI. 

This SQL formatter/beautifier supports keywords from SQL-92, SQL-99, SQL-2003, SQL-2008, SQL-2011 and PostgreSQL specifics keywords. Works with any other databases too.

- [pgFormatter @ GitHub](https://github.com/darold/pgFormatter).]]>
            </summary>
            <updated>2025-09-15T13:34:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10166</id>
            <title type="text"><![CDATA[pgEdge]]></title>
            <link rel="alternate" href="https://www.pgedge.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10166"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[pgEdge is the open source Enterprise Postgres company.

pgEdge delivers PostgreSQL solutions for maximum high availability, ultra-low latency, zero downtime maintenance, and data residency across deployment options and cloud regions. Single instances can be scaled up to active-active (multi-master) distributed deployments in a matter of minutes, giving you the freedom and flexibility to shift your data needs for your business instantly.

- [pgEdge @ GitHub](https://github.com/pgedge).

Related contents:

- [pgEdge goes Open Source @ pgEdge](https://www.pgedge.com/blog/pgedge-goes-open-source).]]>
            </summary>
            <updated>2025-09-12T12:29:25+00:00</updated>
        </entry>
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