Salesforce Data Graphs - Best Practices, Limits & Guardrails — 2026 Edition
Naming note : Salesforce has rebranded Data Cloud as Data 360. This post uses the new name; everything here applies to orgs still seeing the old label. What a Data Graph really is A Data Graph is a pre-computed, denormalized view of your customer data. You pick a primary Data Model Object (DMO) inside a Data Space, attach related DMOs, calculated insights, and segment memberships, and Data 360 joins all of that into a single read-only JSON blob per primary key. That blob is what gets queried - not the underlying tables - which is why Data Graphs can return sub-second responses even when the source data spans hundreds of millions of rows. High-level architecture: bounded inputs flow into a pre-computed graph, which many consumers read cheaply. There are two flavours, and the difference matters more than most teams realize on day one: • Near real-time Data Graph - the default. Refreshes on a schedule (every 30 minutes on Marketing Cloud data graphs, hourly, every 4 hours, daily, weekly,...