Batch to Streaming in One Easy Step

Last edited on Oct 21, 2024
In this talk we will demonstrate how to get started with streaming analytics using the same analytics engineering skillset that keeps you productive in batch analytics.
Traditionally, streaming analytics has required a separate knowledge base, tooling, and ecosystem from batch analytics, one that is comparatively poorer as an ecosystem with a lot less tooling.
We believe that the future of streaming is the same as that of batch analytics - using dbt and SQL for modeling and working with your data. In this talk, we’ll walk through how Materialize helps you build a SQL-first streaming pipeline, as well as go through real-life examples of how Materialize users are building streaming pipelines in production with the very same dbt models they built for their batch data.
Get started in dbt
Join the analytics engineers building data infrastructure that actually scales.
Install dbt Wizard CLI
Get started with an agent purpose-built for analytics engineering. It knows which tool to call, which context to pull, and checks its own work before surfacing anything to you.



