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    <title>InfoQ - Apache Iceberg</title>
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      <title>Article: The Schema Proliferation Problem in Kafka and Flink Pipelines: How to Solve It</title>
      <link>https://www.infoq.com/articles/schema-proliferation-problem/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Apache+Iceberg</link>
      <description>&lt;img src="https://res.infoq.com/articles/schema-proliferation-problem/en/headerimage/schema-proliferation-problem-header-1779270222602.jpg"/&gt;&lt;p&gt;Schema proliferation builds slowly and gets expensive fast. One schema per event type feels right until there are ten tables, union queries spanning all of them, and a single field rename touching every schema. Discriminator-based schema consolidation collapses that to two tables, turning multi-table unions into a single query, while new variants are additive and don't break existing consumers.&lt;/p&gt; &lt;i&gt;By Spoorthi Basu&lt;/i&gt;</description>
      <category>Java</category>
      <category>Apache Kafka</category>
      <category>Apache Iceberg</category>
      <category>Schema</category>
      <category>Apache Flink</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>article</category>
      <pubDate>Mon, 25 May 2026 13:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/schema-proliferation-problem/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Apache+Iceberg</guid>
      <dc:creator>Spoorthi Basu</dc:creator>
      <dc:date>2026-05-25T13:00:00Z</dc:date>
      <dc:identifier>/articles/schema-proliferation-problem/en</dc:identifier>
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    <item>
      <title>Google Cloud Introduces Cross-Engine Iceberg Support in BigQuery</title>
      <link>https://www.infoq.com/news/2026/05/google-cross-engine-iceberg/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Apache+Iceberg</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/05/google-cross-engine-iceberg/en/headerimage/generatedHeaderImage-1778071626715.jpg"/&gt;&lt;p&gt;At the Apache Iceberg Summit last month, Google announced new interoperability features for Apache Iceberg in BigQuery. The preview of the serverless Iceberg REST catalog lets teams create, update, and query the same Apache Iceberg tables in BigQuery and in engines like Spark, Flink, and Trino without duplicating data.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>Google BigQuery</category>
      <category>Cloud</category>
      <category>Data Lake</category>
      <category>Google Cloud</category>
      <category>Apache Iceberg</category>
      <category>Data Portability</category>
      <category>Data Catalog</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Sat, 23 May 2026 08:42:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/google-cross-engine-iceberg/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Apache+Iceberg</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-05-23T08:42:00Z</dc:date>
      <dc:identifier>/news/2026/05/google-cross-engine-iceberg/en</dc:identifier>
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