Beyond the monolithic CDP
The traditional CDP bundles data storage, processing, and activation into a single monolithic platform. The composable CDP flips this model: your existing data warehouse becomes the data plane while the CDP provides orchestration, identity resolution, and activation as a control plane.
Why monolithic CDPs create problems
Traditional CDPs copy your customer data into their own storage, creating data silos and duplicate storage costs. Every sync introduces latency, and every vendor migration means re-ingesting terabytes of data.
The composable architecture
In a composable CDP, the data warehouse (Snowflake, BigQuery, Databricks) serves as the single source of truth. The CDP sits on top as a control plane that handles:
- Identity resolution — matching and merging profiles using warehouse-native computation
- Segmentation — compiling segment definitions to SQL that executes on your warehouse
- Activation — pushing audiences to downstream tools from the warehouse
Fitting into the modern data stack
Composable CDPs integrate naturally with dbt, Airflow, and cloud-native warehouses. They treat the warehouse as the canonical data store rather than duplicating it.
When composable makes sense
The composable approach works best for organizations with a mature data warehouse and engineering team. For teams without warehouse infrastructure, a traditional CDP may still be the faster path.
Read the full article on WiseAnalytics.