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Traditional CDP vs. Adobe RTCDP:where the architecture diverges
Traditional CDP approach
Adobe RTCDP composable approach
Data must be ingested and replicated into the CDP to be used for activation
Federated Audience Composition queries warehouse data in place — no replication, no profile bloat, no governance exposure
Segments are evaluated on nightly batch cycles, creating 24-48 hour latency between signal and action
Streaming segmentation evaluates segment membership as events arrive — suppressing and triggering fire within minutes
Person-centric identity graphs struggle with B2B multi-contact, multi-site account structures
B2B Edition introduces account-level schemas and deterministic entity resolution for accounts, opportunities, and buying groups
Channel partner data sharing requires raw data transfer, which is commercially and legally difficult to negotiate with distributors
Data Collaboration (Clean Room model) enables shared audience activation without exposing raw data on either side
AI/ML pipelines are built separately from the data governance layer; compliance review happens post-deployment
Data usage labels and consent policies enforced at the activation layer; governance is structural, not a retrofit
Identity resolution treated as a one-time configuration task at deployment
Ongoing entity resolution with monitoring tools; identity hygiene is an operational discipline, not a checkbox
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