Advanced SQL

Chapter 3. Architecting SQL-Driven Solutions

So far, we’ve traveled the SQL journey from its evolution and expanding capabilities in Chapter 1, to advanced query techniques and performance optimization strategies in Chapter 2. Now it is time to turn our focus to better understand how those queries fit into scalable, SQL-centered architectures. For mid- to senior-level practitioners, the role extends beyond simply writing queries, since it often involves shaping the design of entire systems and orchestrating data pipelines that rely heavily on SQL as their foundation.

In this chapter, we’ll explore the principles behind architecting SQL-driven solutions, namely, how to build modular and maintainable data pipelines, decide between batch and streaming approaches, structure the layers of a modern data platform, and avoid common architectural issues. We will introduce concepts such as data mesh and data products for scaling data ownership across teams and data contracts as the formal agreements that ensure reliability, quality, and consistency between producers and consumers.

We will also address operational considerations that make a system production-ready, such as testing, observability, and continuous integration/continuous delivery (CI/CD) practices for SQL pipelines, and leveraging infrastructure-as-code for managing cloud resources. Whether you’re working in a traditional RDBMS or a cloud native warehouse, this chapter will also help you think holistically about data systems ...