Cloud Information Model

an application-agnostic data model that simplifies integration and accelerates innovation.

Key Takeaways

• CIM is an open, application-agnostic data model — a shared vocabulary of business concepts (customers, orders, products, and so on) that lets different cloud and on-premises systems exchange data without bespoke point-to-point mapping.
• It exists to solve a specific, expensive problem: every application ships its own data model, so integration teams end up writing and maintaining custom translation code that is brittle and slows innovation.
• It is governed as an open standard, produced by a consortium and open sourced under the Joint Development Foundation, part of the Linux Foundation — so anyone can contribute, review, and adopt it.
• Content is organized into Subject Areas (domains), each representing a major business concept, with designs published in multiple formats including example diagrams.
• CIM is a model, not a product. It defines meaning and structure; you still choose how to map, store, and move data in your own systems.

A New Standard for Data Interoperability

CIM is produced by an open consortium formed to deliver a standards-based solution for connecting enterprise products. With CIM, you can create seamless and tailored personal experiences across cloud-native applications.

To accelerate digital transformation and deliver personalized engagements to customers across every channel, many companies adopt multiple cloud and on-premises applications. Each comes with its own data model, which forces developers to build, test, and manage custom code that’s necessary to map and translate data across different systems. Instead of accelerating digital transformation, this process slows innovation and leads to brittle integrations.

CIM is a modern, open specification to help ease the pain of integrating data. CIM provides a defined standard to communicate easily between different data formats. Open sourced as part of the Joint Development Foundation (under the Linux Foundation), we welcome any and all contributors.

Why Application-Specific Data Models Break Down

The core problem CIM addresses is not that any single application has a bad data model. Most are perfectly reasonable within their own boundaries. The problem is the combinatorial explosion that happens when you connect many of them.

Consider a typical enterprise stack: a CRM, an ERP, a marketing automation platform, a support desk, a data warehouse, and a handful of line-of-business SaaS tools. If each system has its own notion of “customer,” “account,” “order,” and “product,” then every pair of systems that needs to share data requires its own mapping. The number of integrations grows roughly with the square of the number of systems, and each mapping is a small, undocumented, unowned piece of logic that someone must maintain forever.

The symptoms are familiar to anyone who has run an integration practice:

• Semantic drift. “Customer” in the CRM means a billing entity; in the support desk it means a person who files tickets. The same word, two meanings, silently reconciled by a mapping nobody remembers writing.
• Brittle pipelines. A vendor renames a field or changes an enum, and an ETL job fails at 2 a.m. because the mapping was hard-coded against the old shape.
• Duplicated effort. Two teams independently build near-identical translations between the same two systems because there is no shared reference to point at.
• Vendor lock-in by data. Migrating off a platform is expensive not because of the software but because of the accumulated translation logic tied to its schema.

A shared, application-agnostic model attacks the root cause: instead of N-to-N mappings, each system maps once to a common model, and the common model carries the meaning.

What “Application-Agnostic” Actually Means

It is worth being precise about the design philosophy, because “agnostic” is often used loosely.

An application-agnostic model is not owned by, or optimized for, any single vendor’s product. It describes business concepts in terms that would be recognizable to a domain expert — a customer, an order, a product, a location — rather than in terms that mirror one application’s internal tables. That neutrality is what makes it a useful hub: no participant has to adopt a competitor’s worldview to interoperate.

This is the same architectural instinct behind other neutral interchange standards. Just as the Resource Description Framework (RDF) and schema.org give the web a shared vocabulary for describing things, and just as EDI and later UBL (Universal Business Language, an OASIS standard) gave supply chains a shared format for transactions, CIM aims to give enterprise applications a shared vocabulary for their core business entities. The difference is scope and modernity: CIM targets the connected, API-driven, cloud-and-on-premises world rather than batch file exchange.

A useful mental model is the canonical data model pattern from enterprise integration, popularized in Gregor Hohpe and Bobby Woolf’s Enterprise Integration Patterns. CIM is, in effect, a collaboratively maintained canonical model — the “hub” in a hub-and-spoke integration topology — but one that is open, versioned, and shared across organizations rather than invented privately inside one company.

How CIM Is Organized: Subject Areas and Domains

Collaboratively defined content is organized into domains, or Subject Areas. Each Subject Area represents a major business concept. The CIM designs are available in multiple formats for each domain, including example diagrams. The number and scope of the Subject Areas will grow with the consortium and contributions.

In practice, this means you should think of CIM as a library of related models rather than a single monolithic schema. Typical Subject Areas cluster around recognizable business concerns — for example, parties and accounts, products and catalogs, orders and transactions, and the relationships that tie them together. Because each area is published with diagrams and machine-readable definitions, different teams can adopt different areas at different times without waiting for the whole model to be complete.

A few practical implications follow from this structure:

• Adopt incrementally. You do not need to map your entire enterprise to CIM on day one. Start with the Subject Area that hurts most — usually the customer or order domain — and expand.
• Extend rather than fork. When CIM lacks a concept you need, the open model is designed to be extended. Contributing an extension back is preferable to maintaining a private fork, because a fork drifts and loses the interoperability benefit.
• Treat diagrams as documentation, not the source of truth. The example diagrams are for humans; the machine-readable definitions are what your tooling should consume.

CIM in the Integration Landscape: How to Decide

CIM is one option among several for taming integration complexity. Choosing well requires matching the tool to the problem. The table below contrasts the main approaches an enterprise data architect typically weighs.

Approach	What it is	Best when	Main trade-off
Point-to-point mapping	Custom code translating directly between two systems	Only two systems, stable schemas, short horizon	Does not scale; N-to-N explosion; brittle
Canonical model (e.g., CIM)	A shared, neutral model each system maps to once	Many systems, cross-vendor, long-lived integration	Upfront modeling effort; governance needed
Vendor iPaaS connectors	Prebuilt connectors from an integration platform	Common SaaS pairs, speed over control	Connector-specific semantics; potential lock-in
Industry interchange standards (EDI, UBL, HL7, etc.)	Domain-specific message formats	Regulated or well-established verticals	Narrow scope; often batch-oriented
Data virtualization / federation	Query across sources without centralizing	Analytics, read-mostly access	Does not resolve semantic conflicts by itself

The decision heuristic is straightforward: if you have more than a handful of systems that must agree on the meaning of shared entities, and those systems come from different vendors, a canonical model pays for itself. If you have two systems and no plans to add more, point-to-point is fine. If your need is purely analytical and read-only, federation may suffice — but note that federation moves the semantic problem rather than solving it.

CIM is complementary to, not a replacement for, the tools around it. An ETL or ELT pipeline (built with something like Apache Airflow, dbt, or a commercial platform) still does the moving; CIM defines what the data means once it arrives. A message broker such as Apache Kafka still does the transporting; CIM defines the shape of the events. The model is the contract; the tooling is the plumbing.

Governance, Licensing, and Why the Foundation Matters

CIM is open sourced as part of the Joint Development Foundation, which operates under the Linux Foundation. This is not a trivial detail — it is central to why an enterprise can safely build on CIM.

The Linux Foundation is a well-established neutral home for collaborative open-source projects, and the Joint Development Foundation provides a lightweight legal structure for developing standards and specifications collaboratively. Hosting CIM there means:

• Neutral stewardship. No single vendor controls the model, so adopting it does not mean adopting a competitor’s roadmap.
• Open contribution. Anyone — vendors, enterprises, individual contributors — can propose changes, and the process is transparent.
• Predictable licensing. Foundation-hosted specifications typically carry terms designed for broad, royalty-friendly adoption, which matters enormously to legal and procurement teams evaluating a standard.

For an architect making the case internally, this governance story is often as important as the technical content. “It’s an open standard under the Linux Foundation” answers the questions that kill standards adoption: Who controls it? What happens if a vendor exits? Can we contribute our extensions?

Getting Started: A Practical Adoption Path

Adopting a shared model is as much an organizational exercise as a technical one. A pragmatic sequence looks like this:

1. Inventory your shared entities. Identify the business concepts that appear in more than one system — usually customer, product, order, and location. These are your candidates.
2. Pick one Subject Area and one integration. Choose the highest-pain, lowest-blast-radius integration to prove the model. A single reporting pipeline or one new application onboarding is ideal.
3. Map each system to CIM once. Build the translation from each source system to the CIM representation, and from CIM to each target. Resist the urge to map system-to-system directly.
4. Document your extensions. Where CIM does not cover a concept, record the extension explicitly and consider contributing it back.
5. Establish ownership. A canonical model without a steward decays. Assign a team or role responsible for the mappings and for tracking upstream changes.
6. Version and test. Treat the model and its mappings as versioned artifacts with tests, exactly as you would application code.

The most common failure mode is treating CIM as a one-time modeling exercise rather than a living contract. The organizations that succeed treat the model the way they treat an API: versioned, tested, owned, and evolved deliberately.

Partners Contributing to CIM

CIM is a consortium effort, and its value grows with participation. Partners contribute Subject Area content, review proposals, and help shape the direction of the model. Because the work is open, contributions are not limited to large vendors — enterprises with real integration pain and individual practitioners with domain expertise are equally welcome.

Get in Touch

Are you interested in joining the CIM initiative? Great! Please feel free to email us for more information. Email Us.

Frequently Asked Questions

What is the Cloud Information Model (CIM)?

CIM is an application-agnostic, open-source data model that provides a shared, standards-based vocabulary for the business concepts enterprises need to exchange across cloud and on-premises applications. It is produced by an open consortium and hosted under the Joint Development Foundation, part of the Linux Foundation. Its purpose is to reduce the custom mapping code that brittle point-to-point integrations require.

Is CIM a product or a specification?

CIM is a specification — a model and a set of definitions — not a runnable product. It defines the meaning and structure of shared entities; you still choose your own ETL/ELT tooling, message brokers, and storage. Think of it as the contract that your integration plumbing implements, rather than the plumbing itself.

How is CIM different from a vendor’s integration platform?

An integration platform (an iPaaS or connector library) moves data and often ships prebuilt connectors, but those connectors encode vendor-specific semantics. CIM is neutral and vendor-independent, so it does not lock you into one platform’s worldview. The two are complementary: you can use CIM as the canonical model inside any integration platform.

What are Subject Areas in CIM?

Subject Areas (also called domains) are the organizing units of the model, each representing a major business concept such as customers, products, or orders. Designs are published in multiple formats, including example diagrams, and the set of Subject Areas is expected to grow as the consortium and community contribute more content.

Can we extend CIM if it doesn’t cover our concepts?

Yes. CIM is designed to be extended, and because it is open source under a neutral foundation, you can propose additions through the contribution process. Extending the shared model and contributing back is strongly preferable to maintaining a private fork, which drifts over time and forfeits the interoperability benefit that motivated adopting CIM in the first place.

Who should adopt CIM?

It is most valuable to organizations running many applications from different vendors that must agree on the meaning of shared entities — the classic situation for enterprise data architects and integration engineers. Application and platform vendors also benefit by aligning their schemas to a neutral model, which makes their products easier for customers to integrate. If you have only two stable systems, simpler point-to-point mapping may be sufficient.

Further reading

• Linux Foundation — Wikipedia
• Joint Development Foundation — Wikipedia
• Enterprise Integration Patterns — Wikipedia
• Resource Description Framework (RDF) — Wikipedia