Data 360 vs Customer Data Platforms

Data 360, formerly Data Cloud, is Salesforce's customer data platform; third-party sources such as Salesforce Ben trace its lineage through names including Salesforce CDP and Customer 360 Audiences. It is not the only way to build a unified customer view. Many organisations use a standalone CDP, and many build on their data warehouse with a "composable" or warehouse-native pattern.

This guide compares the three approaches fairly. Product claims are attributed to the vendor that makes them. There is no universal winner; the right choice depends on where your data lives, where it is used and who will run it. For the narrower question of Data 360 versus a warehouse alone, see Data 360 vs a traditional data warehouse.

The three approaches

Data 360. Salesforce describes it as a unified data and context layer for CRM, analytics and AI agents. It ingests data into Data Lake Objects, maps it to the Customer 360 Data Model, resolves identities and activates segments. Its main draw is native use inside Salesforce: Marketing Cloud Next and Salesforce Personalization build on it, and Salesforce positions it as a context layer for AI agents such as Agentforce.

Standalone CDP. An independent platform that collects events and profiles from many sources and sends audiences to many destinations. Examples include Segment, mParticle by Rokt and Tealium, which Braze lists among its CDP partners. Their strengths are typically breadth of connectors and independence from any single application suite; check each vendor's documentation for specifics.

Warehouse-native or composable. The data warehouse (for example Snowflake, BigQuery, Databricks or Redshift) is the system of record for customer data. Reverse ETL tools such as Census and Hightouch, both listed by Braze, push modelled data to applications. Some engagement platforms read the warehouse directly: Braze's Cloud Data Ingestion syncs from warehouses, and its Connected Sources query the warehouse "without copying the underlying data to Braze".

How the gap is narrowing

These categories overlap. Data 360 offers zero copy federation with Snowflake, Databricks, Redshift and BigQuery, so it can work with warehouse data without copying all of it. Salesforce lists query federation, Live Query and optional Cached Acceleration; file federation is labelled "In Beta Now" on its page, and BigQuery expansion was announced as "GA Fall 2026". Some warehouse-native tools also offer identity and audience features; check each vendor's documentation. Compare current capabilities, not category labels.

When each approach fits

Data 360 fits when

• Salesforce is where most customer action happens: CRM, service, Marketing Cloud Next, personalisation or Agentforce.
• You want unified profiles available to agents and flows without building an integration for each.
• Your team is stronger in Salesforce administration than in data engineering.

A standalone CDP fits when

• Your engagement and analytics tools come from many vendors, and Salesforce is one destination among several.
• You want customer data independent of any one application suite.
• Event collection across many sites and apps is the main requirement.

Warehouse-native fits when

• Your warehouse is already the trusted source, with a capable data engineering team.
• Analytics and data science use the same data as marketing.
• You prefer to pay for warehouse compute and choose each tool separately.

Combining approaches

Approaches can be mixed: the warehouse as the analytical source, Data 360 federating from it for Salesforce use cases, and an engagement platform such as Braze reading the warehouse for its own audiences. The design question becomes which system owns identity and consent. Pick one owner for each and document it; see our Customer 360 architecture.

Migration notes

Moving to Data 360 from a standalone CDP. Inventory the CDP's sources, destinations, identity rules and computed traits. Map traits to calculated insights, audiences to segments and destinations to activation targets, confirming each target in current Salesforce Help. Run both in parallel and reconcile profile and audience counts before switching any destination.

Adding Data 360 to a warehouse-native estate. Start with zero copy where the warehouse is supported, and ingest only what needs Data 360 processing. Agree whether identity is resolved in the warehouse or in Data 360; resolving in both without a rule produces conflicting profiles.

Moving away from Data 360. Export unified profiles and link objects, document identity and reconciliation rules, and rebuild consent handling first, since sends depend on it.

In every case, plan for consent, retention and deletion to move with the data, and check obligations with your legal adviser.

How we help

GeekMidst offers Data 360 consulting and data engineering services. We assess the options against your requirements, sources and team, and we say where an approach outside Salesforce fits better.

Sources

• https://www.salesforce.com/data/
• https://www.salesforce.com/data/connectivity/zero-copy/
• https://braze.com/docs/partners/home
• https://www.braze.com/docs/user_guide/data/cloud_ingestion
• https://developer.salesforce.com/docs/data/data-cloud-dev/guide/dc-object-model.html