Meet the challenge of storing and accessing analytic data in SQL Server with speed and efficiencynow 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 managementwithout 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.

Solve analytic performance issues with columnstore indexes in SQL Server Create, use, and maintain columnstore indexes for high-performance analytics Apply best practices for fast, scalable, and cost-effective analytic workloads in SQL Server

Autorentext

Edward Pollack is a Microsoft Data Platform MVP with a passion for learning how Data Platforms work and sharing that knowledge with the community. His experiences in data architecture, database design, performance optimization, and data security are motivation for public speaking, writing, coding, and other community activities. Ed has spoken at SQL Saturday events, SQL Bits, PASS Summit, EightKB, and many other regional and international events. Ed is the organizer of the Capital Area SQL Server Group and SQL Saturday Albany, as well as a co-organizer of SQL Saturday New York City, and Future Data Driven. He has published a number of books, including Dynamic SQL: Applications, Performance, and Security in Microsoft SQL Server, Expert Performance Indexing in Azure SQL and SQL Server 2022, and Analytics Optimization with Columnstore Indexes in Microsoft SQL Server: Optimizing OLAP Workloads. Ed is also an active contributor of content to SimpleTalk. In his free time, Ed enjoys video games, traveling, cooking exceptionally spicy foods, and hanging out with his amazing wife and sons.

Inhalt

1. Introduction to Analytic Data in a Transactional Database.- 2. Transactional vs. Analytic Workloads.- 3. What are Columnstore Indexes?.- 4. Columnstore Index Architecture.- 5. Columnstore Compression.- 6. Columnstore Metadata.- 7. Batch Execution.- 8. Bulk Loading Data.- 9. Delete and Update Operations.- 10. Segment and Rowgroup Elimination.- 11. Partitioning.- 12. Non-Clustered Columnstore Indexes on Rowstore Tables.- 13. Non-Clustered Rowstore Indexes on Columnstore Tables.- 14. Columnstore Index Maintenance.- 15. Columnstore Index Performance.- 16. Ordered Columnstore Indexes.