<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Big Data on Support Tools</title><link>https://support.tools/categories/big-data/</link><description>Recent content in Big Data on Support Tools</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Fri, 05 Jun 2026 00:00:00 -0500</lastBuildDate><atom:link href="https://support.tools/categories/big-data/index.xml" rel="self" type="application/rss+xml"/><item><title>Data Lake Architecture with Delta Lake and Apache Iceberg</title><link>https://support.tools/data-lake-architecture-delta-iceberg/</link><pubDate>Fri, 05 Jun 2026 00:00:00 -0500</pubDate><guid>https://support.tools/data-lake-architecture-delta-iceberg/</guid><description>&lt;p&gt;Modern data lake architectures require sophisticated table formats that provide ACID transactions, schema evolution, and time travel capabilities while maintaining the scalability and flexibility of traditional data lakes. Delta Lake and Apache Iceberg represent the next generation of table formats that solve many challenges of traditional data lakes.&lt;/p&gt;</description></item><item><title>Advanced Apache Spark Optimization for Large-Scale Data Processing</title><link>https://support.tools/advanced-spark-optimization-large-scale-processing/</link><pubDate>Fri, 17 Apr 2026 00:00:00 -0500</pubDate><guid>https://support.tools/advanced-spark-optimization-large-scale-processing/</guid><description>&lt;p&gt;Apache Spark has revolutionized big data processing, but achieving optimal performance at scale requires deep understanding of its internals and sophisticated optimization techniques. This comprehensive guide explores advanced Spark optimization strategies that can dramatically improve performance for large-scale data processing workloads.&lt;/p&gt;</description></item></channel></rss>