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Full Description
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.
Contents
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.
