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Book synopsis

Meet the challenge of storing and accessing analytic data in SQL Server with speed and efficiency now with expanded coverage of SQL Server 2025 and Azure SQL Database features. 

This updated second edition also explores how columnstore indexes compare to other modern analytic storage options, helping you make informed architectural decisions. Whether you're optimizing OLAP workloads or modernizing your data platform, this practical guide shows how columnstore indexes deliver faster query performance and enable rapid business intelligence insights.

Inside, you'll find a complete walkthrough of columnstore indexing, from foundational concepts to detailed architecture, implementation, and maintenance strategies. Learn best practices, explore hands-on demonstrations, and uncover common mistakes to avoid. Whether you're new to columnstore or looking to deepen your expertise, this book offers clear, actionable, and definitive guidance for development, testing, and production environments.

Discover how columnstore indexes reduce storage costs, boost performance, and simplify data management without requiring additional licensing. Gain insight into when and how to use them, and how to architect scalable, high-performance analytic solutions in SQL Server.

You Will Learn To:

• Apply best practices for the use and maintenance of analytic data in SQL Server
• Use metadata to understand the size and shape of data
• Load, maintain, and delete data from large analytic tables
• Leverage columnstore compression to save storage, memory, and time
• Choose between columnstore and rowstore indexes
• Avoid performance pitfalls and leverage advanced features

Who This Book Is For

Database developers, administrators, and architects working with large analytic datasets who need a reliable, cost-effective way to improve query performance in SQL Server.

Book details

Book category Books in German Naturwissenschaften, Medizin, Informatik, Technik Informatik, EDV Informatik

• Full title: Analytics Optimization with Columnstore Indexes in Microsoft SQL Server
• Author: Edward Pollack
• Language: English
• Binding: Paperback
• Number of pages: 186
• EAN: 9798868826092
• ID: 51274515
• Publisher: APRESS L.P.
• Weight: 627 g
• Dimensions: 254 × 178 mm
• Date of publishing: 01. August 2026

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