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The relational datastore supports a maximum of 200 tables (schemas).

For Orchestrated campaigns, the total size of any individual schema must not exceed 100 GB.

Daily updates to a schema should be limited to less than 20% of its total record count to maintain performance and stability.

Relational data is the primary model supported for ingestion, data modeling, and segmentation use cases.

Schemas used for targeting must contain at least one identity field of type String, mapped to a defined identity namespace.

Profile + relational data ingestion is required.

All ingestion must occur via Change Data Capture sources:

• For File-based: change_type field is required.

• For Cloud-based: Table logging must be enabled.

Direct updates to Snowflake or datasets are not supported. The system is read-only, all changes must be applied through Change Data Capture.

ETL processes are not supported. Data must be fully transformed into the required format prior to ingestion.

Partial updates are not allowed, each row must be provided as a complete record.

Batch ingestion for Campaign Orchestration is limited to once every 15 minutes.

Ingestion latency, time from ingestion to availability in Snowflake, typically ranges from 15 minutes to 2 hours, depending on:

• Data volume

• System concurrency

• Type of operation, e.g. inserts are faster than updates

All schemas, including fact tables, must include a version descriptor to ensure proper version control and traceability.

Each table must have a defined primary key to support data integrity and downstream operations.

The table_name assigned during dataset creation is permanent and is used throughout segmentation and personalization features.

Field groups are not supported in the current data modeling framework.

Only scalar attributes are supported in audience definitions; maps and arrays are not allowed.

Segmentation activities primarily relies on relational data. While profile data can be included, using large profile datasets may impact performance.

Limits are enforced on the number of profile attributes that can be used in both batch and streaming audiences to maintain system efficiency.

List of Values (LOVs) and enumerations are fully supported.

Read Audiences are not cached, each campaign execution triggers a full audience evaluation from the underlying data.

Optimization is strongly recommended when working with large or complex audience definitions to ensure performance.

Saved audiences activites are static, they reflect the data available at the time of campaign execution.

Appending to a Saved Audience activity is not supported. Any modifications require a full overwrite of the audience.