Implementing the CQRS Pattern | Spice.ai Demo

Command Query Responsibility Segregation (CQRS) is a powerful pattern for scaling read-heavy, data-intensive applications. In this step-by-step walkthrough, you’ll learn how to simplify CQRS using Spice AI’s local materialization and acceleration to dramatically boost query performance without adding architectural complexity. In this demo, you’ll learn how to: - Replicate and accelerate data from PostgreSQL using a single Spice runtime - Chain a second runtime to materialize and accelerate views on top of the first - Benchmark read performance and compare: • Direct PostgreSQL queries • Spice acceleration • Spice acceleration + materialized views - Achieve sub-10ms response times on the same dataset You’ll see real response time histograms and side-by-side benchmarks showing how Spice reduces load on your primary database, speeds up read paths, and delivers a lightweight, high-throughput CQRS architecture. Explore the complete CQRS example in the Spice Cookbook and run it end-to-end yourself: https://github.com/spiceai/cookbook/blob/trunk/cqrs/README.md Join the Spice Slack community to connect with other users and learn more: http://spiceai.org/slack