A domain-centric data platform built around one core insight: the domain is the right unit of abstraction for managing data at scale. Not the individual model (too granular), not the project (too vague) — the business domain, as defined by Data Mesh principles.
About the Project
dmp-cloud provides production-grade dbt development capabilities: native scheduling, domain-level metrics, lineage visualization, observability, and a web-based IDE — all through an analyst-friendly interface that hides infrastructure complexity.
What dmp-cloud Is
- Domain Observability Platform — see domain health, cross-domain impact, and failure alerts without building custom dashboards
- Pre-built Metrics Layer — saves 40+ hours of engineering time vs DIY
- Analyst-Friendly Web IDE — GUI replaces CLI for dbt development
- Native Scheduler — no external orchestrator required
What dmp-cloud Is Not
- Not a managed Airflow competitor (Astronomer, MWAA)
- Not a head-on dbt Cloud alternative
- Not an infrastructure play
- Not a transformation framework replacement (SQLMesh)
Key Capabilities
- Domain-Level Observability — monitor health across domains, track cross-domain dependencies, get alerts before downstream failures cascade
- Built-In Metrics Layer — define, version, and serve metrics at the domain level without stitching together custom tooling
- Web-Based dbt IDE — analysts write and test models in the browser; no CLI, no local setup, no DevOps tickets
- Native Scheduling — run dbt jobs on schedule directly from the platform, without wiring up Airflow, Dagster, or cron
- Lineage Visualization — understand how data flows between domains and models at a glance
How It Relates to DMP.AF
dmp-cloud is the managed evolution of DMP.AF. Where DMP.AF is an open-source library you self-host with Airflow, dmp-cloud is a full platform that removes the need for external orchestration and infrastructure management entirely.
