Use the best-in-class analytics engineering workflows of dbt to manage revolutionary new streaming data capabilities in Materialize.
Keep the SQL modelling conventions your team is familiar with.
dbt run
once and your views are continually kept updated.
Write tests that run continually on your data and alert immediately.
dbt is a SQL-based transformation workflow that lets teams quickly and collaboratively deploy analytics code following software engineering best practices.
Materialize is a fast, distributed, SQL database built on streaming internals.
Manage Materialize using dbt in Three Steps
Maintain the entire schema of your SQL transformations (sources, views, materialized views) in a dbt project in a git repo.
Execute `dbt run` from the CLI to build the SQL models and transformations in Materialize once, and to migrate after updates.
Materialize automatically updates the results of SQL transformations as source data changes. Results can be queried in SQL or streamed out.
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