Data 360 vs Adobe Real-Time CDP: the CDP comparison the warehouse debates skip

Every comparison we’ve written about Data 360 so far has been against a data platform — Snowflake, Databricks, Microsoft Fabric. Those are the debates a data-engineering team has. But there’s a second buyer who never enters that room, and they’re asking a completely different question: not “warehouse or lakehouse,” but “which customer data platform do we standardize on to unify profiles and activate audiences” — and for that buyer the shortlist is almost always Salesforce Data 360 versus Adobe Real-Time CDP.

That comparison rarely gets written honestly, because most of what’s published is one vendor’s battlecard wearing a blog’s clothes. So here’s the version we’d give a marketing and data team with both vendors in the room: what each actually is under the hood, how they resolve identity, where the real-time story is genuinely different, and why the decision comes down to a center of gravity that has nothing to do with which demo looked slicker.

First, the naming — because it’s a real source of confusion

Salesforce renamed Data Cloud to Data 360 at Dreamforce in October 2025, folding it under the broader Agentforce 360 platform brand as the data layer that grounds agents. It’s a naming change, not a re-architecture — same product, same license, same data model — and in practice both names still circulate: Salesforce’s own developer docs and URLs still say “data-cloud,” and third parties write “Data 360 (formerly Data Cloud).” We covered what Data 360 is in depth; for this post, know that “Data 360” and “Salesforce Data Cloud” are the same thing.

Adobe’s product is Adobe Real-Time CDP (Real-Time Customer Data Platform), an application built on Adobe Experience Platform (AEP) — the same foundation as Adobe Journey Optimizer, Customer Journey Analytics, and the rest of Experience Cloud. That lineage is the whole story with Adobe, as we’ll see.

Two architectures, two centers of gravity

The single most important thing to understand is that these platforms were built from opposite ends of the customer.

Data 360 is CRM-native and lakehouse-shaped. Its storage is a native open lakehouse built on Apache Iceberg and Parquet in object storage — the same substrate we unpacked in the Iceberg file-federation post. Data lands as Data Lake Objects in native schema, gets mapped and harmonized into Data Model Objects against Salesforce’s standardized Customer 360 data model, and external warehouse data can be linked as External DLOs for zero-copy access without moving it. There’s a two-tier store underneath: the lakehouse for scale and batch, plus a low-latency store that holds materialized Data Graphs — pre-joined denormalized profile views — for millisecond retrieval. Zero-copy federation is a first-class pattern here, not an afterthought.

Adobe Real-Time CDP is experience-native and schema-first. Everything conforms to XDM (Experience Data Model) — denormalized schemas built on XDM Individual Profile and ExperienceEvent classes. And the storage model is genuinely different: Adobe runs two physically separate stores. The AEP Data Lake (on Microsoft Azure) holds catalog and historical data, queryable via SQL through Query Service; the Real-Time Customer Profile lives in a separate low-latency store (Azure Cosmos DB), holding a denormalized union-schema profile. Data flows Edge Network → Data Lake → Real-Time Customer Profile, with a separate Identity Service graph stitching it together. Adobe’s zero-copy analogue, Federated Audience Composition, exists but is narrower than Salesforce’s zero-copy federation.

The two data flows side by side make the difference concrete:

Data 360 — CRM-native open lakehouse
  sources ─▶ Data Lake Objects ─map▶ Data Model Objects (Customer 360 model)
                                       ├─▶ lakehouse (Iceberg + Parquet, object storage)
                                       └─▶ low-latency store ─▶ Data Graphs (ms retrieval → agents/CRM)
  external warehouses ─zero-copy▶ External DLOs (queried in place, not copied)

Adobe Real-Time CDP — experience-native, XDM schema-first
  sources ─▶ Edge Network ─▶ AEP Data Lake (Azure; history, SQL via Query Service)
                             └─▶ Real-Time Customer Profile (Azure Cosmos DB)
  Identity Service ─▶ Identity Graph (stitches identities across channels)

The contrast in one line: Data 360 is an open-format lakehouse with zero-copy as a design principle, anchored to the CRM; Adobe RTCDP is a prescriptive XDM-schema platform with a purpose-built profile store, anchored to the experience/marketing stack. Adobe demands more schema discipline up front and rewards it with a tightly engineered real-time profile; Data 360 is more flexible about ingestion and leans on the open table format and the CRM data model.

Identity resolution: rules-driven vs graph-driven

Both platforms unify fragmented records into a single customer, but the mechanics differ in a way that matters for how you reason about correctness.

Data 360 is explicitly rules-driven. You define an identity resolution ruleset of match rules (which source records collapse into one profile) and reconciliation rules (which field value wins when sources disagree, settable at object or field level). The output is a Unified Individual plus a link object that maps every source ID back to the unified ID — an auditable bridge, which is exactly the discipline we argued for in identity resolution in Data 360. You can read the rules, reason about why two records merged, and change the logic deliberately.

Adobe is graph-driven through its Identity Service, which builds an Identity Graph stitching identifiers across devices and channels; enterprises can build a private graph from their own deterministic data. One precision point worth getting right, because vendor comparisons routinely botch it: the Identity Service that RTCDP uses is primarily deterministic. Adobe does have probabilistic/algorithmic stitching technology in its broader cooperative device-graph offerings, but that is not the default behavior of RTCDP’s identity resolution. If someone tells you “Adobe does probabilistic matching and Salesforce doesn’t,” they’re conflating Adobe’s wider identity portfolio with the CDP’s actual default — treat both platforms’ enterprise identity as fundamentally deterministic and rule/graph-based.

Real-time: this is where the honest difference lives

“Real-time” is in both product names, and it’s the claim most worth scrutinizing because it’s where they genuinely diverge.

Adobe’s real-time story is built on a distributed Edge Network with published characteristics: per Adobe’s documentation, the Edge supports high inbound event throughput (on the order of thousands of events per second) and edge segmentation that can qualify a profile in roughly a few hundred milliseconds from event entry — fast enough for same-session personalization on a web property. Adobe exposes three activation modes: batch, streaming, and edge. That edge tier, purpose-built for anonymous-visitor and on-site experience use cases, is historically Adobe’s strongest card.

Data 360’s real-time story is shaped differently. It centers on real-time ingestion — streaming data in as micro-batches so it’s quickly available — feeding the materialized Data Graphs in the low-latency store that agents and CRM processes read for fast retrieval. The design goal is less “qualify an anonymous web visitor mid-session at the edge” and more “give an agent or a service rep a current, pre-joined profile in milliseconds without running a live warehouse query.”

Be skeptical of the marketing on both sides here. Adobe’s edge figures come from its own documentation; Salesforce’s “millisecond” claims are largely blog-level rather than a contractual SLA. The honest framing: if your primary need is same-session, edge-speed personalization of web experiences for largely anonymous traffic, Adobe’s Edge Network is the more mature engine. If your primary need is a current unified profile to ground CRM workflows and agents, Data 360’s real-time ingestion plus Data Graphs is built for exactly that. They’re both “real-time”; they’re optimized for different real-time jobs.

Activation: breadth vs native depth

A CDP is only as useful as where it can send an audience, and this is a clean split.

Adobe has the broader, more mature independent destinations catalog — advertising platforms, email and marketing tools, cloud storage, and on-site personalization — with profile-export, streaming-export, and edge-personalization destination types, plus public destinations for everyone and private destinations for its top tier. It also offers RTCDP Collaboration, a data-clean-room capability for advertiser–publisher matching. If your activation is heavily ad-tech and cross-channel to non-Adobe endpoints, Adobe’s catalog is deep.

Data 360’s activation is strongest into the Salesforce estate — Marketing Cloud, CRM apps, Ad Audiences (a paid add-on for ad-platform activation), and Data Actions/webhooks — with segmentation and activation native to the ecosystem. If your downstream is Salesforce-centric and your endgame is grounding agents and orchestrating CRM journeys, that native depth beats a broad catalog you’d have to integrate anyway.

The AI layer: both have one, pointed at different work

Neither platform is just a data store anymore; both bolted an agentic layer on top, and the shape reveals their priorities.

Data 360’s AI story is that it grounds Agentforce — the CRM-native advantage. An agent retrieves a customer’s purchase history, churn score, loyalty tier, and case context from Data 360’s real-time Data Graphs, which is exactly the semantic-layer grounding that keeps an agent citing governed data instead of guessing. One data platform, one agent platform, one stack.

Adobe embeds agents into the experience workflow: an in-product AI Assistant, the Adobe Experience Platform Agent Orchestrator (launched March 2025) for building and coordinating agents, purpose-built agents like an Audience Agent inside RTCDP, and Brand Concierge for consumer-facing conversational experiences that look up and enrich the real-time profile. Adobe’s agents are pointed at marketing and experience orchestration; Salesforce’s are pointed at the full CRM surface — sales, service, commerce, and marketing.

Pricing: both consumption, both worth modeling before you sign

Neither is a per-seat product, and both reward you for understanding the meter before you commit.

Data 360 bills on consumption — credits for ingest, unify, segment, activate, ground, and insights — with storage billed separately and premium capabilities (Data Spaces, real-time profiles, Ad Audiences) priced as add-ons. As of purchases and renewals after February 24, 2026, Salesforce lets you choose Data Services credits, Flex Credits (a universal currency shared across Data 360, Agentforce, and Slack), or Profile-Based Pricing (a flat per-profile bundle). The recurring practitioner complaint is real and worth heeding: consumption costs can spiral without governance, which is the whole reason we wrote up credit optimization and the pricing-and-credits mechanics in detail.

Adobe Real-Time CDP is quote-based — no public price list — and priced primarily per 1,000 Person Profiles, across B2C, B2B, and B2P editions, each in a Prime or Ultimate tier, with overage fees if you exceed your committed profile count. Any specific dollar figure you see for Adobe in a third-party article is an estimate, not a published rate. The structural difference for a buyer: Data 360 spend keys off data and activity volume; Adobe spend keys off your profile count. A business with a huge addressable audience but modest per-profile activity will model those two meters very differently.

Where each genuinely fits

Strip away the battlecards and the fit is about which ecosystem you’ve already bet on.

• Choose Data 360 when Salesforce CRM is your system of record, you want unified data flowing natively into Sales, Service, Marketing, and Agentforce, and grounding agents is on your roadmap. It’s especially strong for B2B and for aligning sales/service with marketing. Run it far outside the Salesforce estate and you pay a “suite tax” in custom configuration.
• Choose Adobe Real-Time CDP when you’re a large B2C brand already committed to Adobe Experience Cloud — Journey Optimizer, Customer Journey Analytics, AEM, Target — and your priority is edge-speed, experience-led personalization and broad ad activation. Run it heavily alongside non-Adobe tools and you’ll feel the third-party integration friction and the XDM learning curve.

Both create meaningful lock-in. That’s not a knock — it’s the nature of a CDP that sits at the center of your customer data. The decision isn’t “which is better in the abstract”; it’s “which ecosystem is my center of gravity, and which CDP disappears into it.” If the honest answer is “we’re a Salesforce shop building toward agents,” the warehouse comparisons and this one point the same way. If it’s “we’re an Adobe experience shop optimizing web personalization,” Adobe’s home-field advantages are real and you should weigh them at full strength.

The takeaway

The warehouse comparisons ask whether Data 360 can replace your lakehouse; the answer there is usually “it complements it over an open format.” This comparison asks a different question, and the answer is cleaner than either vendor wants it to be: these are two CDPs with opposite anchors. Data 360 is CRM-native, lakehouse-shaped, rules-driven on identity, zero-copy by design, and built to ground Agentforce. Adobe Real-Time CDP is experience-native, XDM-schema-first, graph-driven on identity, edge-optimized for same-session personalization, and built to power Adobe’s journey and activation stack. Pick the one whose center of gravity matches yours, model the consumption meter honestly before you sign, and don’t let a demo of the other platform’s best trick talk you out of the ecosystem you actually live in.

Understanding the basics

Is Salesforce Data 360 the same as Data Cloud?

Yes. Salesforce renamed Data Cloud to Data 360 at Dreamforce in October 2025, positioning it as the data layer of the Agentforce 360 platform. It’s a naming change, not a re-architecture — the product, license, integrations, and data model are the same. Both names still circulate in mid-2026: Salesforce’s own docs and URLs often still say “Data Cloud,” and third parties write “Data 360 (formerly Data Cloud).” Adobe’s competing product is Adobe Real-Time CDP, built on Adobe Experience Platform.

What’s the biggest architectural difference between Data 360 and Adobe Real-Time CDP?

Their center of gravity and their storage model. Data 360 is CRM-native, built on an open Apache Iceberg lakehouse with zero-copy federation as a first-class pattern, and unifies data into Salesforce’s Customer 360 data model. Adobe Real-Time CDP is experience-native, requires data to conform to its XDM schema, and runs two physically separate stores — an Azure data lake for historical data and a low-latency Cosmos DB store for the real-time profile — fed through its Edge Network. Data 360 leans on open formats and the CRM; Adobe leans on prescriptive schemas and a purpose-built profile store.

Which is better for real-time personalization?

It depends on the job. Adobe’s Edge Network is purpose-built for same-session, edge-speed personalization of web experiences and anonymous-visitor use cases, and it’s historically the stronger engine for that. Data 360’s real-time story centers on real-time ingestion plus materialized Data Graphs that deliver a current unified profile for grounding CRM workflows and Agentforce agents. Both are “real-time,” but Adobe optimizes for edge web personalization while Data 360 optimizes for a fast, governed profile inside the Salesforce ecosystem.

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Trying to decide whether your customer data belongs in Data 360, an Adobe stack, or a warehouse behind zero-copy — and want the identity rules and activation right before it grounds anything? Talk to us. Getting the data foundation right for CRM and agents is exactly the work we do.