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dbt Mesh is a multi-project pattern for governed cross-team data products

About dbt Mesh

2023 docs introducing dbt Mesh: cross-project refs, Catalog, groups, access, versions, and contracts for independent yet aligned teams.

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About dbt Mesh | dbt Developer Hub

dbt Labs
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The extract states that organizations outgrow a single dbt project when coordination, dependencies, and governance across teams lack a first-class path. Mesh is introduced as a pattern from converging features: cross-project {{ ref() }} on Enterprise plans, Catalog with cross-project lineage, governance of model access, groups with owners, access configs, model versions, and model contracts on data shape.

For mature data platforms, the page’s trigger conditions include model counts that slow development and teams that have already formed separate domains. The guidance is to treat shared models as stable APIs, using versions for adoption and deprecation and contracts so upstream changes do not silently break downstream products.

Governed shared meaning across systems is the mesh interface: public models, explicit owners, contracted shapes, and versioned change. Autonomy and collaboration are held together by those shared definitions rather than by merging every team into one project.

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Abstract

The page says a single dbt project struggles at scale to coordinate stakeholders, and Mesh addresses multi-project dependencies, governance, and workflows. Mesh is a pattern, not one product: Enterprise cross-project ref, Catalog lineage, governance, groups, access, model versions, and contracts. It recommends treating models as stable APIs when coordinating across teams and outlines when multi-project architecture becomes appropriate.

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dbt meshcross-project refgovernancecontractsmodel versionscatalogData GovernanceData ContractsData EngineeringSemantic Interoperability
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