dbt + Materialize:
Real-Time Data Superpowers
Use the best-in-class analytics engineering workflows of dbt to manage revolutionary new streaming data capabilities in Materialize.
Keep your Standard SQL
Keep the SQL modelling conventions your team is familiar with.
End Manual Orchestration
dbt run once and your views are continually kept updated.
Get Event-Driven Capabilities
Write tests that run continually on your data and alert immediately.
"With Materialize, we can write real-time SQL, the same way as we already are in Snowflake with batch while continuing to use dbt."
What is dbt?
dbt is a SQL-based transformation workflow that lets teams quickly and collaboratively deploy analytics code following software engineering best practices.
- Git-enabled version control
- Modularity
- CI/CD
- Documentation
What is Materialize?
Materialize is a fast, distributed, SQL database built on streaming internals.
- Incremental Computation Engine
- Presents as Postgres
- Built for Joins
- Event-Driven Primitives
How it works?
Manage Materialize using dbt in Three Steps
Write SQL transformations in dbt
Maintain the entire schema of your SQL transformations (sources, views, materialized views) in a dbt project in a git repo.
Use the dbt CLI to build views in Materialize
Execute `dbt run` from the CLI to build the SQL models and transformations in Materialize once, and to migrate after updates.
Results are automatically kept up-to-date
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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