Optimize query performance for Azure Cosmos DB for NoSQL

Learn how to optimize query performance by analyzing query patterns, configuring range and composite indexes, selecting vector index types, and choosing consistency levels that balance freshness with cost efficiency.

Learning objectives

After completing this module, you'll be able to:

• Analyze query patterns and use metrics to identify performance bottlenecks and missing indexes.
• Configure range and composite indexes to optimize filter and sort operations for AI retrieval patterns.
• Select the appropriate vector index type based on dataset size, accuracy requirements, and performance goals.
• Design indexing policies that balance read performance against write costs for your workload profile.
• Choose consistency levels that meet application requirements while minimizing RU consumption.