Despite having many advantages, XML structure imposes several major obstacles to large document processing. Incompatibility between the linear nature of the current algorithms such as caching and prefetch used in operating systems and databases, and the non-linear structure of XML data makes XML processing more costly. Also depth-first (DF) structure of XML documents is a significant overhead to processing applications, including search engines. Recent research on XML query processing has learned that sibling clustering can improve performance significantly. However, the existing methods are limited in several aspects including in processing very large documents. In this book, a better data organization has been introduced for native XML databases, named sibling-first (SF), that significantly improves the performance in large data processing. The parse-free SF storage has been implemented in virtual memory as well as a format on disk. Experimental results with real data have shown that significantly higher performance can be achieved when XPath queries are conducted on very large SF documents.