Technical writing on reliable AI systems, query optimization, and cloud data infrastructure.https://barzanmozafari.com/https://barzanmozafari.com/blog/why-slower-sql-can-make-your-dbt-pipeline-faster/https://barzanmozafari.com/blog/why-slower-sql-can-make-your-dbt-pipeline-faster/Modern analytics is increasingly organized as recurring SQL pipelines rather than isolated SQL statements. Tools like dbt have gained extreme popularity in recent years, allowing teams to write each transformation as SQL and make dependencies between transformations explicit. This has led to directed acyclic graphs (DAGs) with hundreds or thousands of interdependent SQL models. Traditional query optimizers and source-to-source query rewriters are not effective at optimizing these expensive pipelines. In this post, we explore how DAGSmith treats these explicit dependencies as optimization signals and uses an LLM to find pipeline-level refactorings and optimize a dbt project holistically. Mon, 14 Sep 2026 00:00:00 GMTdbtquery rewritingdatabase optimizationsnowflakedatabricksBarzan Mozafari