3 Best-Selling Database Partitioning Books Millions Love

The breakthrough moment came when Arun Kumar distilled complex Oracle database storage concepts into a concise, accessible guide. You learn how to create table clusters, define cluster keys, and manage range partition tables, with practical steps like partitioning existing tables and creating partition indexes. This book suits database professionals and developers seeking focused, hands-on knowledge about Oracle's storage structures rather than broad database theory. Its 48-page format delivers targeted insights ideal for those wanting to optimize Oracle table and index space usage without wading through excess detail.

IBM Redbooks brings its extensive mainframe and database expertise to this technical guide focused on DB2 9's partitioning capabilities. You’ll gain a detailed understanding of how to implement database partitioning, table partitioning, and multidimensional clustering (MDC) to optimize performance and manage large datasets effectively. The book dives into real-world IBM DB2 environments, explaining concepts like partitioning keys and data distribution strategies, making it especially relevant for database administrators and architects working within IBM systems. While it assumes some familiarity with DB2, the book’s detailed approach helps you grasp how partitioning can reduce query times and improve scalability.

This personalized book explores battle-tested methods for optimizing database partitioning performance, tailored specifically to your expertise and goals. It covers fundamental concepts and advanced techniques that match your background, delving into the nuances of partitioning approaches that enhance data management efficiency. By focusing on your interests, this book reveals practical insights into partitioning schemes, key performance factors, and real-world challenges, making complex topics accessible and relevant. It combines proven knowledge with a customized perspective, offering a focused learning experience that empowers you to master partitioning strategies relevant to your unique use cases and objectives.

This book challenges the usual focus on XML data management by zeroing in on the overlooked yet crucial aspect of partitioning large XML documents. Saud Alotaibi and Salahadin Adam introduce PIXSS, a novel system that divides and indexes voluminous XML files into manageable chunks, speeding up processing and backup tasks. You’ll find detailed explanations of new algorithms designed specifically for querying partitioned XML data, backed by experimental results that prove significant performance gains. This work suits database engineers and software developers who handle large-scale XML datasets and want to optimize storage and retrieval beyond traditional indexing methods.