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Standard schemas are hierarchical schemas that use classes and field groups to capture record or time-series data.

A standard schema is composed of:

• A class (which defines the data behavior: record or time-series).
• One or more field groups (which add specific fields to the schema).

In Journey Optimizer, standard schemas are typically used to represent individual people and their attributes, capture time-series interactions such as clicks, purchases, or logins, and power Real-Time Customer Profile for segmentation and personalization.

鉃★笍 Learn how to create and configure a standard schema in this video (video)

Relational schemas are flat, non-hierarchical schemas that do not use classes or field groups. They are used to capture record data for relational entities and are primarily used in Journey Optimizer Orchestrated campaigns.

Examples of relational entities include:

• Bookings, contracts, or subscriptions
• Products or catalogs
• Stores, locations, or partners

With relational schemas, you can send one message per entity (e.g., per booking, per subscription), create segments based on entity attributes (e.g., product category, store location), and improve addressability by reaching all contacts linked to an entity.

How relational schemas work:

1. Create schemas manually or import via DDL
2. Link schemas to define relationships between entities and people (e.g., loyalty transactions linked to members, rewards linked to brands).
3. Ingest data into your dataset from supported sources.

鉃★笍 Learn how to manage relational schemas and datasets
鉃★笍 Get started with Orchestrated campaigns