- vs Terraform
- vs Airflow
- vs Databricks
vs Infrastructure as Code
Infrastructure as Code tools excel at provisioning. You declare what you want, they create it. But what happens after?Terraform / Pulumi
- Provisions infrastructure
- Changes require manual cascade
- Dependencies resolved at build-time
- Best for static infrastructure
pragma-os
- Provisions and maintains
- Changes propagate automatically
- Dependencies are runtime reactive
- Best for dynamic data infrastructure
The key difference: IaC provisions once. When your warehouse changes, you manually update dependent projects and run
terraform apply again. pragma-os maintains continuously—changes propagate automatically through your dependency graph.When to Use pragma-os
Multiple Tools
Your stack includes BigQuery, dbt, vector databases, and more. You need them to work together.
Dynamic Dependencies
When your warehouse changes, your transformations should adapt. When your source evolves, your pipelines should respond.
Product Focus
You’d rather ship features than chase cascading configuration changes.
No Platform Team
You need platform-team capabilities without hiring a platform team.
When pragma-os Might Not Be Right
You only need one tool
You only need one tool
If you’re just using BigQuery, use BigQuery directly. pragma-os adds value when you’re coordinating multiple systems.
Your infrastructure is completely static
Your infrastructure is completely static
If nothing changes after initial setup, Terraform works fine. pragma-os shines when infrastructure is dynamic.
You have a mature platform team
You have a mature platform team
If you’ve built internal tooling that handles dependency propagation, you might not need to adopt something new.
Summary
pragma-os solves maintenance
It’s not a replacement for Terraform, Airflow, or Snowflake—it’s what ties them together and keeps them in sync as your infrastructure evolves.