Large Tables, Big Problems: Indexing, Partitioning, and Archiving at Scale

When your tables reach tens or hundreds of millions of rows, traditional performance strategies start to break down. In this session, we’ll tackle the challenges of working with large and ever-growing tables, with a focus on both query performance and data retention.
You’ll learn:
• How to tune queries and indexes for large-rowset access patterns
• Using partitioning for both performance and maintenance
• Choosing between compression, filtered indexes, and columnstore
• Archival strategies: hot/warm/cold data separation, table splitting, and offloading
• Real-world examples of archiving with automation, partition switching, and hybrid storage models
Whether you're managing operational workloads or analytical systems, this session will give you practical techniques to keep your largest tables efficient, scalable, and under control.

You’ll learn: • How to tune queries and indexes for large-rowset access patterns • Using partitioning for both performance and maintenance • Choosing between compression, filtered indexes, and columnstore • Archival strategies: hot/warm/cold data separation, table splitting, and offloading • Real-world examples of archiving with automation, partition switching, and hybrid storage models